Ola Spjuth

Designing microplate layouts using artificial intelligence

Francisco Rodríguez, María Andreína; Carreras-Puigvert, Jordi; Spjuth, Ola

Part of Artificial Intelligence in the Life Sciences, 2023

• DOI for Designing microplate layouts using artificial intelligence
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Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection

Seal, Srijit; Carreras-Puigvert, Jordi; Trapotsi, Maria-Anna; Yang, Hongbin et al.

Part of Communications Biology, 2022

• DOI for Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection
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Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects

Rietdijk, Jonne; Aggarwal, Tanya; Georgiev, Polina; Lapins, Maris et al.

Part of Science of the Total Environment, 2022

• DOI for Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects
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Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction

Olsson, Henrik; Kartasalo, Kimmo; Mulliqi, Nita; Capuccini, Marco et al.

Part of Nature Communications, 2022

• DOI for Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
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A phenomics approach for antiviral drug discovery

Rietdijk, Jonne; Tampere, Marianna; Pettke, Aleksandra; Georgiev, Polina et al.

Part of BMC Biology, 2021

• DOI for A phenomics approach for antiviral drug discovery
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Deep-learning models for lipid nanoparticle-based drug delivery

Harrison, Philip J.; Wieslander, Håkan; Sabirsh, Alan; Karlsson, Johan et al.

Part of Nanomedicine, p. 1097-1110, 2021

• DOI for Deep-learning models for lipid nanoparticle-based drug delivery

Predicting With Confidence: Using Conformal Prediction in Drug Discovery

Alvarsson, Jonathan; Arvidsson McShane, Staffan; Norinder, Ulf; Spjuth, Ola

Part of Journal of Pharmaceutical Sciences, p. 42-49, 2021

• DOI for Predicting With Confidence: Using Conformal Prediction in Drug Discovery
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Machine Learning Strategies When Transitioning between Biological Assays

Arvidsson McShane, Staffan; Ahlberg, Ernst; Noeske, Tobias; Spjuth, Ola

Part of Journal of Chemical Information and Modeling, p. 3722-3733, 2021

• DOI for Machine Learning Strategies When Transitioning between Biological Assays
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Conformal prediction enables disease course prediction and allows individualized diagnostic uncertainty in multiple sclerosis

Sreenivasan, Akshai Parakkal; Vaivade, Aina; Noui, Yassine; Emami Khoonsari, Payam et al.

Part of npj Digital Medicine, 2025

• DOI for Conformal prediction enables disease course prediction and allows individualized diagnostic uncertainty in multiple sclerosis
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Cell Painting: a decade of discovery and innovation in cellular imaging.

Seal, Srijit; Trapotsi, Maria-Anna; Spjuth, Ola; Singh, Shantanu et al.

Part of Nature Methods, p. 254-268, 2025

• DOI for Cell Painting: a decade of discovery and innovation in cellular imaging.

Associations of PFAS and OH-PCBs with risk of multiple sclerosis onset and disability worsening

Vaivade, Aina; Erngren, Ida; Carlsson, Henrik; Freyhult, Eva et al.

Part of Nature Communications, 2025

• DOI for Associations of PFAS and OH-PCBs with risk of multiple sclerosis onset and disability worsening
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Data management of scientific applications in a reinforcement learning-based hierarchical storage system

Zhang, Tianru; Gupta, Ankit; Francisco Rodríguez, María Andreína; Spjuth, Ola et al.

Part of Expert systems with applications, p. 121443-121443, 2024

• DOI for Data management of scientific applications in a reinforcement learning-based hierarchical storage system

Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank

Seal, Srijit; Spjuth, Ola; Hosseini-Gerami, Layla; Garcia-Ortegon, Miguel et al.

Part of Journal of Chemical Information and Modeling, p. 1172-1186, 2024

• DOI for Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank
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Conformal prediction enables disease course prediction and allows individualized diagnostic uncertainty in multiple sclerosis

Sreenivasan, Akshai Parakkal; Vaivade, Aina; Noui, Yassine; Emami Khoonsari, Payam et al.

Part of npj Digital Medicine, 2025

• DOI for Conformal prediction enables disease course prediction and allows individualized diagnostic uncertainty in multiple sclerosis
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Cell Painting: a decade of discovery and innovation in cellular imaging.

Seal, Srijit; Trapotsi, Maria-Anna; Spjuth, Ola; Singh, Shantanu et al.

Part of Nature Methods, p. 254-268, 2025

• DOI for Cell Painting: a decade of discovery and innovation in cellular imaging.

Associations of PFAS and OH-PCBs with risk of multiple sclerosis onset and disability worsening

Vaivade, Aina; Erngren, Ida; Carlsson, Henrik; Freyhult, Eva et al.

Part of Nature Communications, 2025

• DOI for Associations of PFAS and OH-PCBs with risk of multiple sclerosis onset and disability worsening
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Data management of scientific applications in a reinforcement learning-based hierarchical storage system

Zhang, Tianru; Gupta, Ankit; Francisco Rodríguez, María Andreína; Spjuth, Ola et al.

Part of Expert systems with applications, p. 121443-121443, 2024

• DOI for Data management of scientific applications in a reinforcement learning-based hierarchical storage system

Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank

Seal, Srijit; Spjuth, Ola; Hosseini-Gerami, Layla; Garcia-Ortegon, Miguel et al.

Part of Journal of Chemical Information and Modeling, p. 1172-1186, 2024

• DOI for Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank
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Federated learning for predicting compound mechanism of action based on image-data from cell painting

Ju, Li; Hellander, Andreas; Spjuth, Ola

Part of Artificial Intelligence in the Life Sciences, 2024

• DOI for Federated learning for predicting compound mechanism of action based on image-data from cell painting
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Data management of scientific applications in a reinforcement learning-based hierarchical storage system

Zhang, Tianru; Gupta, Ankit; Francisco Rodríguez, María Andreína; Spjuth, Ola et al.

Part of Expert systems with applications, 2024

• DOI for Data management of scientific applications in a reinforcement learning-based hierarchical storage system
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Improved Detection of Drug-Induced Liver Injury by Integrating Predicted In Vivo and In Vitro Data

Seal, Srijit; Williams, Dominic; Hosseini-Gerami, Layla; Mahale, Manas et al.

Part of Chemical Research in Toxicology, p. 1290-1305, 2024

• DOI for Improved Detection of Drug-Induced Liver Injury by Integrating Predicted In Vivo and In Vitro Data
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CPSign: Conformal Prediction for Cheminformatics Modeling

Arvidsson McShane, Staffan; Norinder, Ulf; Alvarsson, Jonathan; Ahlberg, Ernst et al.

Part of Journal of Cheminformatics, 2024

• DOI for CPSign: Conformal Prediction for Cheminformatics Modeling
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Artificial intelligence for high content imaging in drug discovery

Carreras-Puigvert, Jordi; Spjuth, Ola

Part of Current opinion in structural biology, 2024

• DOI for Artificial intelligence for high content imaging in drug discovery
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New approach methods to assess developmental and adult neurotoxicity for regulatory use: a PARC work package 5 project

Tal, Tamara; Myhre, Oddvar; Fritsche, Ellen; Rüegg, Joëlle et al.

Part of Frontiers in Toxicology, 2024

• DOI for New approach methods to assess developmental and adult neurotoxicity for regulatory use: a PARC work package 5 project
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From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability

Seal, Srijit; Carreras-Puigvert, Jordi; Singh, Shantanu; Carpenter, Anne E. et al.

Part of Molecular Biology of the Cell, 2024

• DOI for From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability
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Combining molecular and cell painting image data for mechanism of action prediction

Tian, Guangyan; Harrison, Philip J.; Sreenivasan, Akshai P.; Carreras-Puigvert, Jordi et al.

Part of Artificial Intelligence in the Life Sciences, p. 100060-100060, 2023

• DOI for Combining molecular and cell painting image data for mechanism of action prediction

Designing microplate layouts using artificial intelligence

Francisco Rodríguez, María Andreína; Carreras-Puigvert, Jordi; Spjuth, Ola

Part of Artificial Intelligence in the Life Sciences, p. 100073-100073, 2023

• DOI for Designing microplate layouts using artificial intelligence

Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data

Seal, Srijit; Yang, Hongbin; Trapotsi, Maria-Anna; Singh, Satvik et al.

Part of Journal of Cheminformatics, 2023

• DOI for Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
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Evaluating the utility of brightfield image data for mechanism of action prediction

Harrison, Philip John; Gupta, Ankit; Rietdijk, Jonne; Wieslander, Håkan et al.

Part of PloS Computational Biology, 2023

• DOI for Evaluating the utility of brightfield image data for mechanism of action prediction
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Development of new approach methods for the identification and characterization of endocrine metabolic disruptors: a PARC project

Braeuning, Albert; Balaguer, Patrick; Bourguet, William; Carreras-Puigvert, Jordi et al.

Part of Frontiers in Toxicology, 2023

• DOI for Development of new approach methods for the identification and characterization of endocrine metabolic disruptors: a PARC project
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In Silico Prediction of Human Clinical Pharmacokinetics with ANDROMEDA by Prosilico: Predictions for an Established Benchmarking Data Set, a Modern Small Drug Data Set, and a Comparison with Laboratory Methods

Fagerholm, Urban; Hellberg, Sven; Alvarsson, Jonathan; Spjuth, Ola

Part of ATLA (Alternatives to Laboratory Animals), p. 39-54, 2023

• DOI for In Silico Prediction of Human Clinical Pharmacokinetics with ANDROMEDA by Prosilico: Predictions for an Established Benchmarking Data Set, a Modern Small Drug Data Set, and a Comparison with Laboratory Methods

Designing microplate layouts using artificial intelligence

Francisco Rodríguez, María Andreína; Carreras-Puigvert, Jordi; Spjuth, Ola

Part of Artificial Intelligence in the Life Sciences, 2023

• DOI for Designing microplate layouts using artificial intelligence
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Combining molecular and cell painting image data for mechanism of action prediction

Tian, Guangyan; Harrison, Philip J.; Sreenivasan, Akshai P.; Carreras-Puigvert, Jordi et al.

Part of ARTIFICIAL INTELLIGENCE IN THE LIFE SCIENCES, 2023

• DOI for Combining molecular and cell painting image data for mechanism of action prediction
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Disease phenotype prediction in multiple sclerosis

Herman, Stephanie; Arvidsson McShane, Staffan; Zhukovsky, Christina; Emami, Payam et al.

Part of iScience, 2023

• DOI for Disease phenotype prediction in multiple sclerosis
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The Impact of Reference Data Selection for the Prediction Accuracy of Intrinsic Hepatic Metabolic Clearance

Fagerholm, Urban; Spjuth, Ola; Hellberg, Sven

Part of Journal of Pharmaceutical Sciences, p. 2645-2649, 2022

• DOI for The Impact of Reference Data Selection for the Prediction Accuracy of Intrinsic Hepatic Metabolic Clearance

A method for Boolean analysis of protein interactions at a molecular level

Raykova, Doroteya; Kermpatsou, Despoina; Malmqvist, Tony; Harrison, Philip J et al.

Part of Nature Communications, 2022

• DOI for A method for Boolean analysis of protein interactions at a molecular level
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An Open-Source Modular Framework for Automated Pipetting and Imaging Applications

Ouyang, Wei; Bowman, Richard W; Wang, Haoran; Bumke, Kaspar E et al.

Part of Advanced biology, 2022

• DOI for An Open-Source Modular Framework for Automated Pipetting and Imaging Applications
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Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection

Seal, Srijit; Carreras-Puigvert, Jordi; Trapotsi, Maria-Anna; Yang, Hongbin et al.

Part of Communications Biology, 2022

• DOI for Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection
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SimVec: predicting polypharmacy side effects for new drugs

Lukashina, Nina; Kartysheva, Elena; Spjuth, Ola; Virko, Elizaveta et al.

Part of Journal of Cheminformatics, 2022

• DOI for SimVec: predicting polypharmacy side effects for new drugs
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Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects

Rietdijk, Jonne; Aggarwal, Tanya; Georgiev, Polina; Lapins, Maris et al.

Part of Science of the Total Environment, 2022

• DOI for Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects
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In Silico Predictions of the Gastrointestinal Uptake of Macrocycles in Man Using Conformal Prediction Methodology

Fagerholm, Urban; Hellberg, Sven; Alvarsson, Jonathan; Spjuth, Ola

Part of Journal of Pharmaceutical Sciences, p. 2614-2619, 2022

• DOI for In Silico Predictions of the Gastrointestinal Uptake of Macrocycles in Man Using Conformal Prediction Methodology

Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction

Olsson, Henrik; Kartasalo, Kimmo; Mulliqi, Nita; Capuccini, Marco et al.

Part of Nature Communications, 2022

• DOI for Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
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Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening

Schaal, Wesley; Ameur, Adam; Olsson-Strömberg, Ulla; Hermansson, Monica et al.

Part of Cancer Informatics, p. 1-8, 2022

• DOI for Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening
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From biomedical cloud platforms to microservices: next steps in FAIR data and analysis

Sheffield, Nathan C.; Bonazzi, Vivien R.; Bourne, Philip E.; Burdett, Tony et al.

Part of Scientific Data, 2022

• DOI for From biomedical cloud platforms to microservices: next steps in FAIR data and analysis
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In silico predictions of the human pharmacokinetics/toxicokinetics of 65 chemicals from various classes using conformal prediction methodology

Fagerholm, Urban; Hellberg, Sven; Alvarsson, Jonathan; Spjuth, Ola

Part of Xenobiotica, p. 113-118, 2022

• DOI for In silico predictions of the human pharmacokinetics/toxicokinetics of 65 chemicals from various classes using conformal prediction methodology

Predicting protein network topology clusters from chemical structure using deep learning

Sreenivasan, Akshai P.; Harrison, Philip J; Schaal, Wesley; Matuszewski, Damian J. et al.

Part of Journal of Cheminformatics, 2022

• DOI for Predicting protein network topology clusters from chemical structure using deep learning
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Deep learning and conformal prediction for hierarchical analysis of large-scale whole-slide tissue images

Wieslander, Håkan; Harrison, Philip J.; Skogberg, Gabriel; Jackson, Sonya et al.

Part of IEEE journal of biomedical and health informatics, p. 371-380, 2021

• DOI for Deep learning and conformal prediction for hierarchical analysis of large-scale whole-slide tissue images
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Approaches for containerized scientific workflows in cloud environments with applications in life science

Spjuth, Ola; Capuccini, Marco; Carone, Matteo; Larsson, Anders et al.

Part of F1000 Research, p. 513-513, 2021

• DOI for Approaches for containerized scientific workflows in cloud environments with applications in life science

A phenomics approach for antiviral drug discovery

Rietdijk, Jonne; Tampere, Marianna; Pettke, Aleksandra; Georgiev, Polina et al.

Part of BMC Biology, 2021

• DOI for A phenomics approach for antiviral drug discovery
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Deep-learning models for lipid nanoparticle-based drug delivery

Harrison, Philip J.; Wieslander, Håkan; Sabirsh, Alan; Karlsson, Johan et al.

Part of Nanomedicine, p. 1097-1110, 2021

• DOI for Deep-learning models for lipid nanoparticle-based drug delivery

Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology

Fagerholm, Urban; Hellberg, Sven; Spjuth, Ola

Part of Molecules, 2021

• DOI for Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology
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Integrating Statistical and Machine-Learning Approach for Meta-Analysis of Bisphenol A-Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival

Lukashina, Nina; Williams, Michael J.; Kartysheva, Elena; Virko, Elizaveta et al.

Part of International Journal of Molecular Sciences, 2021

• DOI for Integrating Statistical and Machine-Learning Approach for Meta-Analysis of Bisphenol A-Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
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Comparison between lab variability and in silico prediction errors for the unbound fraction of drugs in human plasma

Fagerholm, Urban; Spjuth, Ola; Hellberg, Sven

Part of Xenobiotica, p. 1095-1100, 2021

• DOI for Comparison between lab variability and in silico prediction errors for the unbound fraction of drugs in human plasma
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In silico prediction of volume of distribution of drugs in man using conformal prediction performs on par with animal data-based models

Fagerholm, Urban; Hellberg, Sven; Alvarsson, Jonathan; Arvidsson McShane, Staffan et al.

Part of Xenobiotica, p. 1366-1371, 2021

• DOI for In silico prediction of volume of distribution of drugs in man using conformal prediction performs on par with animal data-based models

Machine Learning Strategies When Transitioning between Biological Assays

Arvidsson McShane, Staffan; Ahlberg, Ernst; Noeske, Tobias; Spjuth, Ola

Part of Journal of Chemical Information and Modeling, p. 3722-3733, 2021

• DOI for Machine Learning Strategies When Transitioning between Biological Assays
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Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit

Blamey, Ben; Toor, Salman; Dahlö, Martin; Wieslander, Håkan et al.

Part of GigaScience, p. 1-14, 2021

• DOI for Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit
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scConnect: a method for exploratory analysis of cell–cell communication based on single-cell RNA-sequencing data

Jakobsson, Jon E. T.; Spjuth, Ola; Lagerström, Malin C.

Part of Bioinformatics, p. 3501-3508, 2021

• DOI for scConnect: a method for exploratory analysis of cell–cell communication based on single-cell RNA-sequencing data
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The machine learning life cycle and the cloud: implications for drug discovery.

Spjuth, Ola; Frid, Jens; Hellander, Andreas

Part of Expert Opinion on Drug Discovery, p. 1071-1079, 2021

• DOI for The machine learning life cycle and the cloud: implications for drug discovery.

Synergy conformal prediction applied to large-scale bioactivity datasets and in federated learning

Norinder, Ulf; Spjuth, Ola; Svensson, Fredrik

Part of Journal of Cheminformatics, 2021

• DOI for Synergy conformal prediction applied to large-scale bioactivity datasets and in federated learning
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Assessing the calibration in toxicological in vitro models with conformal prediction

Morger, Andrea; Svensson, Fredrik; Arvidsson McShane, Staffan; Gauraha, Niharika et al.

Part of Journal of Cheminformatics, 2021

• DOI for Assessing the calibration in toxicological in vitro models with conformal prediction
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Metabolomics: The Stethoscope for the Twenty-First Century

Ashrafian, Hutan; Sounderajah, Viknesh; Glen, Robert; Ebbels, Timothy et al.

Part of Medical principles and practice, p. 301-310, 2021

• DOI for Metabolomics: The Stethoscope for the Twenty-First Century
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ELIXIR and Toxicology: a community in development

Martens, Marvin; Stierum, Rob; Schymanski, Emma L.; Evelo, Chris T. et al.

Part of F1000 Research, p. 1129-1129, 2021

• DOI for ELIXIR and Toxicology: a community in development
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Synergy Conformal Prediction

Gauraha, Niharika; Spjuth, Ola

Part of Proceedings of Machine Learning Research, p. 91-119, 2021

Using Predicted Bioactivity Profiles to Improve Predictive Modeling

Norinder, Ulf; Spjuth, Ola; Svensson, Fredrik

Part of Journal of Chemical Information and Modeling, p. 2830-2837, 2020

• DOI for Using Predicted Bioactivity Profiles to Improve Predictive Modeling

MaRe: Processing Big Data with application containers on Apache Spark

Capuccini, Marco; Dahlö, Martin; Toor, Salman; Spjuth, Ola

Part of GigaScience, 2020

• DOI for MaRe: Processing Big Data with application containers on Apache Spark
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Predicting target profiles with confidence as a service using docking scores

Ahmed, Laeeq; Alogheli, Hiba; Arvidsson Mc Shane, Staffan; Alvarsson, Jonathan et al.

Part of Journal of Cheminformatics, 2020

• DOI for Predicting target profiles with confidence as a service using docking scores
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Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes

Kensert, Alexander; Harrison, Philip J; Spjuth, Ola

Part of SLAS Discovery, p. 466-475, 2019

• DOI for Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes
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Container-based bioinformatics with Pachyderm

Novella, Jon Ander; Emami Khoonsari, Payam; Herman, Stephanie; Whitenack, Daniel et al.

Part of Bioinformatics, p. 839-846, 2019

• DOI for Container-based bioinformatics with Pachyderm

PhenoMeNal: Processing and analysis of metabolomics data in the cloud

Peters, Kristian; Bradbury, James; Bergmann, Sven; Capuccini, Marco et al.

Part of GigaScience, 2019

• DOI for PhenoMeNal: Processing and analysis of metabolomics data in the cloud

On-demand virtual research environments using microservices

Capuccini, Marco; Larsson, Anders; Carone, Matteo; Novella, Jon Ander et al.

Part of PeerJ Computer Science, 2019

• DOI for On-demand virtual research environments using microservices

SciPipe: A workflow library for agile development of complex and dynamic bioinformatics pipelines

Lampa, Samuel; Dahlö, Martin; Alvarsson, Jonathan; Spjuth, Ola

Part of GigaScience, 2019

• DOI for SciPipe: A workflow library for agile development of complex and dynamic bioinformatics pipelines
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Alterations in the tyrosine and phenylalanine pathways revealed by biochemical profiling in cerebrospinal fluid of Huntington's disease subjects

Herman, Stephanie; Niemelä, Valter; Emami Khoonsari, Payam; Sundblom, Jimmy et al.

Part of Scientific Reports, 2019

• DOI for Alterations in the tyrosine and phenylalanine pathways revealed by biochemical profiling in cerebrospinal fluid of Huntington's disease subjects
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Interoperable and scalable data analysis with microservices: Applications in metabolomics

Emami Khoonsari, Payam; Moreno, Pablo; Bergmann, Sven; Burman, Joachim et al.

Part of Bioinformatics, p. 3752-3760, 2019

• DOI for Interoperable and scalable data analysis with microservices: Applications in metabolomics
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Biochemical Differences in Cerebrospinal Fluid between Secondary Progressive and Relapsing-Remitting Multiple Sclerosis

Herman, Stephanie; Åkerfeldt, Torbjörn; Spjuth, Ola; Burman, Joachim et al.

Part of Cells, 2019

• DOI for Biochemical Differences in Cerebrospinal Fluid between Secondary Progressive and Relapsing-Remitting Multiple Sclerosis
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SciPipe - Turning Scientific Workflows into Computer Programs

Lampa, Samuel; Dahlö, Martin; Alvarsson, Jonathan; Spjuth, Ola

Part of Computing in science & engineering (Print), p. 109-113, 2019

• DOI for SciPipe - Turning Scientific Workflows into Computer Programs
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Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty

Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro et al.

Part of Journal of Chemical Information and Modeling, p. 1132-1140, 2018

• DOI for Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty

Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis.

Herman, Stephanie; Emami Khoonsari, Payam; Tolf, Andreas; Steinmetz, Julia et al.

Part of Theranostics, p. 4477-4490, 2018

• DOI for Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis.
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Predicting off-target binding profiles with confidence using Conformal Prediction

Lampa, Samuel; Alvarsson, Jonathan; Arvidsson Mc Shane, Staffan; Berg, Arvid et al.

Part of Frontiers in Pharmacology, 2018

• DOI for Predicting off-target binding profiles with confidence using Conformal Prediction
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Tracking the NGS revolution: managing life science research on shared high-performance computing clusters

Dahlö, Martin; Scofield, Douglas; Schaal, Wesley; Spjuth, Ola

Part of GigaScience, 2018

• DOI for Tracking the NGS revolution: managing life science research on shared high-performance computing clusters
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Evaluating parameters for ligand-based modeling with random forest on sparse data sets

Kensert, Alexander; Alvarsson, Jonathan; Norinder, Ulf; Spjuth, Ola

Part of Journal of Cheminformatics, 2018

• DOI for Evaluating parameters for ligand-based modeling with random forest on sparse data sets
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Efficient iterative virtual screening with Apache Spark and conformal prediction

Ahmed, Laeeq; Georgiev, Valentin; Capuccini, Marco; Toor, Salman et al.

Part of Journal of Cheminformatics, 2018

• DOI for Efficient iterative virtual screening with Apache Spark and conformal prediction

A confidence predictor for logD using conformal regression and a support-vector machine

Lapins, Maris; Arvidsson, Staffan; Lampa, Samuel; Berg, Arvid et al.

Part of Journal of Cheminformatics, 2018

• DOI for A confidence predictor for logD using conformal regression and a support-vector machine
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Novel applications of Machine Learning in cheminformatics

Spjuth, Ola

Part of Journal of Cheminformatics, 2018

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OpenRiskNet, an open e-infrastructure to support data sharing, knowledge integration, in silico analysis and modelling in risk assessment

Oki, Noffisat; Exner, Thomas; Kramer, Stefan; Notredame, Cedric et al.

Part of Abstracts of Papers of the American Chemical Society, 2018

Exploring the usefulness of morphological profiling of cells to study toxicity mechanisms

Georgieva, Polina; Schaal, Wesley; Spjuth, Ola

Part of Toxicology Letters, 2018

• DOI for Exploring the usefulness of morphological profiling of cells to study toxicity mechanisms

OpenRiskNet, an open e-infrastructure to support data sharing, knowledge integration and in silico analysis and modelling in risk assessment

Exner, T. E.; Dokler, J.; Bachler, D.; Farcal, L. R. et al.

Part of Toxicology Letters, 2018

• DOI for OpenRiskNet, an open e-infrastructure to support data sharing, knowledge integration and in silico analysis and modelling in risk assessment

Towards Predicting the Cytochrome P450 Modulation: From QSAR to proteochemometric modeling.

Shoombuatong, Watshara; Prathipati, Philip; Prachayasittikul, Veda; Schaduangrat, Nalini et al.

Part of Current drug metabolism, p. 540-555, 2017

• DOI for Towards Predicting the Cytochrome P450 Modulation: From QSAR to proteochemometric modeling.

The future of metabolomics in ELIXIR.

van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta et al.

Part of F1000 Research, 2017

• DOI for The future of metabolomics in ELIXIR.

RDFIO: extending Semantic MediaWiki for interoperable biomedical data management

Lampa, Samuel; Willighagen, Egon; Kohonen, Pekka; King, Ali et al.

Part of Journal of Biomedical Semantics, 2017

• DOI for RDFIO: extending Semantic MediaWiki for interoperable biomedical data management
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Large-scale virtual screening on public cloud resources with Apache Spark

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin et al.

Part of Journal of Cheminformatics, 2017

• DOI for Large-scale virtual screening on public cloud resources with Apache Spark

The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching

Willighagen, Egon L.; Mayfield, John W.; Alvarsson, Jonathan; Berg, Arvid et al.

Part of Journal of Cheminformatics, 2017

• DOI for The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching
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Mass spectrometry based metabolomics for in vitro systems pharmacology: pitfalls, challenges, and computational solutions.

Herman, Stephanie; Emami Khoonsari, Payam; Aftab, Obaid; Krishnan, Shibu et al.

Part of Metabolomics, 2017

• DOI for Mass spectrometry based metabolomics for in vitro systems pharmacology: pitfalls, challenges, and computational solutions.
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E-Science technologies in a workflow for personalized medicine using cancer screening as a case study

Spjuth, Ola; Karlsson, Andreas; Clements, Mark; Humphreys, Keith et al.

Part of JAMIA Journal of the American Medical Informatics Association, p. 950-957, 2017

• DOI for E-Science technologies in a workflow for personalized medicine using cancer screening as a case study
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Origin of aromatase inhibitory activity via proteochemometric modeling

Simeon, Saw; Spjuth, Ola; Lapins, Maris; Nabu, Sunanta et al.

Part of PeerJ, 2016

• DOI for Origin of aromatase inhibitory activity via proteochemometric modeling
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Recommendations on e-infrastructures for next-generation sequencing

Spjuth, Ola; Bongcam-Rudloff, Erik; Dahlberg, Johan; Dahlö, Martin et al.

Part of GigaScience, 2016

• DOI for Recommendations on e-infrastructures for next-generation sequencing

Large-scale ligand-based predictive modelling using support vector machines

Alvarsson, Jonathan; Lampa, Samuel; Schaal, Wesley; Andersson, Claes et al.

Part of Journal of Cheminformatics, 2016

• DOI for Large-scale ligand-based predictive modelling using support vector machines
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Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles

Lampa, Samuel; Alvarsson, Jonathan; Spjuth, Ola

Part of Journal of Cheminformatics, 2016

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XMetDB: an open access database for xenobiotic metabolism

Spjuth, Ola; Rydberg, Patrik; Willighagen, Egon L.; Evelo, Chris T. et al.

Part of Journal of Cheminformatics, 2016

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Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research

Spjuth, Ola; Krestyaninova, Maria; Hastings, Janna; Shen, Huei-Yi et al.

Part of European Journal of Human Genetics, p. 521-528, 2016

• DOI for Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research
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BioImg.org: A catalog of virtual machine images for the life sciences

Dahlö, Martin; Haziza, Frédéric; Kallio, Aleksi; Korpelainen, Eija et al.

Part of Bioinformatics and Biology Insights, p. 125-128, 2015

• DOI for BioImg.org: A catalog of virtual machine images for the life sciences

A quantitative assessment of the Hadoop framework for analyzing massively parallel DNA sequencing data

Siretskiy, Alexey; Sundqvist, Tore; Voznesenskiy, Mikhail; Spjuth, Ola

Part of GigaScience, 2015

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Privacy-Preservation for Publishing Sample Availability Data with Personal Identifiers

Gholami, Ali; Laure, Erwin; Somogyi, Peter; Spjuth, Ola et al.

Part of Journal of medical and bioengineering, p. 117-125, 2015

• DOI for Privacy-Preservation for Publishing Sample Availability Data with Personal Identifiers

Scaling predictive modeling in drug development with cloud computing

Torabi Moghadam, Behrooz; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin et al.

Part of Journal of Chemical Information and Modeling, p. 19-25, 2015

• DOI for Scaling predictive modeling in drug development with cloud computing

Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from Human Cell Cultures

Grafström, Roland C; Nymark, Penny; Hongisto, Vesa; Spjuth, Ola et al.

Part of ATLA (Alternatives to Laboratory Animals), p. 325-332, 2015

Ligand-Based Target Prediction with Signature Fingerprints

Alvarsson, Jonathan; Eklund, Martin; Engkvist, Ola; Spjuth, Ola et al.

Part of Journal of Chemical Information and Modeling, p. 2647-2653, 2014

• DOI for Ligand-Based Target Prediction with Signature Fingerprints

Benchmarking Study of Parameter Variation When Using Signature Fingerprints Together with Support Vector Machines

Alvarsson, Jonathan; Eklund, Martin; Andersson, Claes; Carlsson, Lars et al.

Part of Journal of Chemical Information and Modeling, p. 3211-3217, 2014

• DOI for Benchmarking Study of Parameter Variation When Using Signature Fingerprints Together with Support Vector Machines

Applications of the InChI in cheminformatics with the CDK and Bioclipse

Spjuth, Ola; Berg, Arvid; Adams, Samuel; Willighagen, Egon

Part of Journal of Cheminformatics, 2013

• DOI for Applications of the InChI in cheminformatics with the CDK and Bioclipse
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On Mechanisms of Reactive Metabolite Formation from Drugs

Claesson, Alf; Spjuth, Ola

Part of Mini-Reviews in medical chemistry, p. 720-729, 2013

• DOI for On Mechanisms of Reactive Metabolite Formation from Drugs

Automated QuantMap for rapid quantitative molecular network topology analysis

Schaal, Wesley; Hammerling, Ulf; Gustafsson, Mats G; Spjuth, Ola

Part of Bioinformatics, p. 2369-2370, 2013

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Lessons learned from implementing a national infrastructure in Sweden for storage and analysis of next-generation sequencing data

Lampa, Samuel; Dahlö, Martin; Olason, Pall I; Hagberg, Jonas et al.

Part of GigaScience, p. 1-10, 2013

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Bioclipse-R: Integrating management and visualization of life science data with statistical analysis

Spjuth, Ola; Georgiev, Valentin; Carlsson, Lars; Alvarsson, Jonathan et al.

Part of Bioinformatics, p. 286-289, 2013

• DOI for Bioclipse-R: Integrating management and visualization of life science data with statistical analysis

WhichCyp: Prediction of Cytochromes P450 Inhibition

Rostkowski, Michal; Spjuth, Ola; Rydberg, Patrik

Part of Bioinformatics, p. 2051-2052, 2013

• DOI for WhichCyp: Prediction of Cytochromes P450 Inhibition

A Unified Proteochemometric Model for Prediction of Inhibition of Cytochrome P450 Isoforms

Lapins, Maris; Worachartcheewan, Apilak; Spjuth, Ola; Georgiev, Valentin et al.

Part of PLOS ONE, 2013

• DOI for A Unified Proteochemometric Model for Prediction of Inhibition of Cytochrome P450 Isoforms
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The ChEMBL database as linked open data

Willighagen, Egon L; Waagmeester, Andra; Spjuth, Ola; Ansell, Peter et al.

Part of Journal of Cheminformatics, p. 23, 2013

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Food for thought...: A toxicology ontology roadmap

Harry, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic et al.

Part of ALTEX. Alternatives zu Tierexperimenten, p. 129-137, 2012

Toxicology Ontology Perspectives

Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic et al.

Part of ALTEX. Alternatives zu Tierexperimenten, p. 139-156, 2012

Accessing, using, and creating chemical property databases for computational toxicology modeling

Williams, Antony J; Ekins, Sean; Spjuth, Ola; Willighagen, Egon L

Part of Methods in molecular biology (Clifton, N.J.), p. 221-241, 2012

• DOI for Accessing, using, and creating chemical property databases for computational toxicology modeling

A novel infrastructure for chemical safety predictions with focus on human health

Spjuth, Ola; Willighagen, Egon; Hammerling, Ulf; Dencker, Lennart et al.

Part of Toxicology Letters, 2012

• DOI for A novel infrastructure for chemical safety predictions with focus on human health

Model building in Bioclipse Decision Support applied to open datasets

Carlsson, Lars; Spjuth, Ola; Eklund, Martin; Boyer, Scott

Part of Toxicology Letters, 2012

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UPPNEX: A solution for next generation sequencing data management and analysis

Lampa, Samuel; Hagberg, Jonas; Spjuth, Ola

Part of EMBnet.journal, p. 44-44, 2012

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Computational toxicology using OpenTox & Bioclipse

Willighagen, Egon; Spjuth, Ola; Grafström, Roland

Part of Toxicology Letters, 2012

• DOI for Computational toxicology using OpenTox & Bioclipse

Open Data, Open Source and Open Standards in chemistry: The Blue Obelisk five years on

O'Boyle, Noel; Guha, Rajarshi; Willighagen, Egon; Adams, Samuel et al.

Part of Journal of Cheminformatics, p. 37, 2011

• DOI for Open Data, Open Source and Open Standards in chemistry: The Blue Obelisk five years on

Linking the Resource Description Framework to cheminformatics and proteochemometrics

Willighagen, Egon; Alvarsson, Jonathan; Andersson, Annsofie; Eklund, Martin et al.

Part of Journal of Biomedical Semantics, p. 6, 2011

• DOI for Linking the Resource Description Framework to cheminformatics and proteochemometrics

Computational toxicology using the OpenTox application programming interface and Bioclipse

Willighagen, Egon; Jeliazkova, Nina; Hardy, Barry; Grafström, Roland et al.

Part of BMC Research Notes, p. 487, 2011

• DOI for Computational toxicology using the OpenTox application programming interface and Bioclipse

Integrated Decision Support for Assessing Chemical Liabilities

Spjuth, Ola; Eklund, Martin; Helgee, Ernst Ahlberg; Boyer, Scott et al.

Part of Journal of chemical information and modeling, p. 1840-1847, 2011

• DOI for Integrated Decision Support for Assessing Chemical Liabilities

Brunn: an open source laboratory information system for microplates with a graphical plate layout design process

Alvarsson, Jonathan; Andersson, Claes; Spjuth, Ola; Larsson, Rolf et al.

Part of BMC Bioinformatics, 2011

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Services for prediction of drug susceptibility for HIV proteases and reverse transcriptases at the HIV Drug Research Centre

Spjuth, Ola; Eklund, Martin; Lapins, Maris; Junaid, Muhammad et al.

Part of Bioinformatics, p. 1719-1720, 2011

• DOI for Services for prediction of drug susceptibility for HIV proteases and reverse transcriptases at the HIV Drug Research Centre

Use of Historic Metabolic Biotransformation Data as a Means of Anticipating Metabolic Sites Using MetaPrint2D and Bioclipse

Carlsson, Lars; Spjuth, Ola; Adams, Samuel; Glen, Robert et al.

Part of BMC Bioinformatics, p. 362, 2010

• DOI for Use of Historic Metabolic Biotransformation Data as a Means of Anticipating Metabolic Sites Using MetaPrint2D and Bioclipse

Towards interoperable and reproducible QSAR analyses: Exchange of data sets

Spjuth, Ola; Willighagen, Egon; Guha, Rajarshi; Eklund, Martin et al.

Part of Journal of Cheminformatics, 2010

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An eScience-Bayes strategy for analyzing omics data

Eklund, Martin; Spjuth, Ola; Wikberg, Jarl

Part of BMC Bioinformatics, p. 282, 2010

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Proteochemometric Modeling of the Susceptibility of Mutated Variants of the HIV-1 Virus to Reverse Transcriptase Inhibitors

Junaid, Muhammad; Lapins, Maris; Eklund, Martin; Spjuth, Ola et al.

Part of PLoS ONE, 2010

• DOI for Proteochemometric Modeling of the Susceptibility of Mutated Variants of the HIV-1 Virus to Reverse Transcriptase Inhibitors

Bioclipse 2.0: Life Science setzt auf die Staerken von Eclipse.

Spjuth, Ola; Alvarsson, Johan; Krachtus, Dieter

Part of Eclipse Magazine, 2009

Bioclipse 2: Towards integrated biocheminformatics

Spjuth, Ola; Alvarsson, Jonathan

Part of EMBnet.news, p. 25-27, 2009

Bioclipse 2: A scriptable integration platform for the life sciences

Spjuth, Ola; Alvarsson, Jonathan; Berg, Arvid; Eklund, Martin et al.

Part of BMC Bioinformatics, p. 397, 2009

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XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services

Wagener, Johannes; Spjuth, Ola; Willighagen, Egon; Wikberg, Jarl

Part of BMC Bioinformatics, p. 279, 2009

• DOI for XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services

The C¹C²: a framework for simultaneous model selection and assessment

Eklund, Martin; Spjuth, Ola; Wikberg, Jarl E S

Part of BMC Bioinformatics, p. 360, 2008

• DOI for The C¹C²: a framework for simultaneous model selection and assessment

Proteochemometric modeling of HIV protease susceptibility

Lapins, Maris; Eklund, Martin; Spjuth, Ola; Prusis, Peteris et al.

Part of BMC Bioinformatics, p. 181, 2008

• DOI for Proteochemometric modeling of HIV protease susceptibility

Bioclipse: an open source workbench for chemo- and bioinformatics

Spjuth, Ola; Helmus, Tobias; Willighagen, Egon L; Kuhn, Stefan et al.

Part of BMC Bioinformatics, p. 59, 2007

• DOI for Bioclipse: an open source workbench for chemo- and bioinformatics
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Eine visuelle Open-Source-Platform für Chemo- und Bioinformatik

Spjuth, Ola

Part of JAVAmagazin, 2006

The LCB Data Warehouse

Ameur, Adam; Yankovski, Vladimir; Enroth, Stefan; Spjuth, Ola et al.

Part of Bioinformatics, p. 1024-1026, 2006

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Using Bioclipse to integrate bioinformatics functionality

Spjuth, Ola

Part of EMBnet.news, p. 5-11, 2005

An Information System for Proteochemometrics

Spjuth, Ola; Eklund, Martin; Wikberg, Jarl

Part of CDK News, p. 54-56, 2005

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Using Iterative MapReduce for Parallel Virtual Screening

Laeeq, Ahmed; Edlund, Åke; Laure, Erwin; Spjuth, Ola

Part of Journal of medical and bioengineering

Predicting With Confidence: Using Conformal Prediction in Drug Discovery

Alvarsson, Jonathan; Arvidsson McShane, Staffan; Norinder, Ulf; Spjuth, Ola

Part of Journal of Pharmaceutical Sciences, p. 42-49, 2021

• DOI for Predicting With Confidence: Using Conformal Prediction in Drug Discovery
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Towards reproducible computational drug discovery

Schaduangrat, Nalini; Lampa, Samuel; Simeon, Saw; Gleeson, Matthew Paul et al.

Part of Journal of Cheminformatics, 2020

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Deep Learning in Image Cytometry: A Review

Gupta, Anindya; Harrison, Philip J.; Wieslander, Håkan; Pielawski, Nicolas et al.

Part of Cytometry Part A, p. 366-380, 2019

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Experiences with workflows for automating data-intensive bioinformatics

Spjuth, Ola; Bongcam-Rudloff, Erik; Carrasco Hernández, Guillermo; Forer, Lukas et al.

Part of Biology Direct, 2015

• DOI for Experiences with workflows for automating data-intensive bioinformatics

Cancer Biology, Toxicology and Alternative Methods Development Go Hand-in-Hand

Kohonen, Pekka; Ceder, Rebecca; Smit, Ines; Vesa, Hongisto et al.

Part of Basic & Clinical Pharmacology & Toxicology, p. 50-58, 2014

• DOI for Cancer Biology, Toxicology and Alternative Methods Development Go Hand-in-Hand

Open source drug discovery with Bioclipse

Spjuth, Ola; Carlsson, Lars; Alvarsson, Jonathan; Georgiev, Valentin et al.

Part of Current Topics in Medicinal Chemistry, p. 1980-1986, 2012

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Introduction to Pharmaceutical Bioinformatics

Wikberg, Jarl; Eklund, Martin; Willighagen, Egon; Spjuth, Ola et al.

Oakleaf Academic, 2010

Data Integration between Swedish National Clinical Health Registries and Biobanks Using an Availability System

Spjuth, Ola; Heikkinen, Jani; Litton, Jan-Eric; Palmgren, Juni et al.

Part of Data Integration in the Life Sciences, p. 32-40, Springer International Publishing, 2014

• DOI for Data Integration between Swedish National Clinical Health Registries and Biobanks Using an Availability System

Chemoinformatics taking Biology into Account: Proteochemometrics

Wikberg, Jarl; Spjuth, Ola; Eklund, Martin; Lapins, Maris

Part of Computational Approaches in Cheminformatics and Bioinformatics, John Wiley & Sons, 2012

• DOI for Chemoinformatics taking Biology into Account: Proteochemometrics

Collaborative Cheminformatics Applications

Guha, Rajarshi; Spjuth, Ola; Willighagen, Egon

Part of Collaborative Computational Technologies for Biomedical Research, John Wiley & Sons, 2011

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Bioclipse: Integration of Data and Software in the Life Sciences

Spjuth, Ola

2009

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Is brightfield all you need for MoA prediction?

Gupta, Ankit; Harrison, Philip J; Wieslander, Håkan; Rietdijk, Jonne et al.

2022

Scalable federated machine learning with FEDn

Ekmefjord, Morgan; Ait-Mlouk, Addi; Alawadi, Sadi; Akesson, Mattias et al.

Part of 2022 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022), p. 555-564, 2022

• DOI for Scalable federated machine learning with FEDn

Synergy Conformal Prediction

Gauraha, Niharika; Spjuth, Ola

Part of Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications, p. 91-110, 2021

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Synergy Conformal Prediction for Regression

Gauraha, Niharika; Spjuth, Ola

Part of Proceedings of the 10th international conference on pattern recognition applications and methods (icpram), p. 212-221, 2021

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A Constraint Programming Approach to Microplate Layout Design

Francisco Rodríguez, María Andreína; Spjuth, Ola

p. 1-3, 2020

Smart Resource Management for Data Streaming using an Online Bin-packing Strategy

Stein, Oliver; Blamey, Ben; Karlsson, Johan; Sabirsh, Alan et al.

Part of 2020 IEEE International Conference on Big Data (Big Data), p. 2207-2216, 2020

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Split knowledge transfer in learning under privileged information framework

Gauraha, Niharika; Söderdahl, Fabian; Spjuth, Ola

Part of Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications, p. 43-52, 2019

Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets

Spjuth, Ola; Brännström, Robin Carrión; Carlsson, Lars; Gauraha, Niharika

Part of Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications, p. 53-65, 2019

Prediction of Metabolic Transformations using Cross Venn-ABERS Predictors

Arvidsson, Staffan; Carlsson, Lars; Paulo, Toccaceli; Spjuth, Ola

Part of Conformal and Probabilistic Prediction with Applications (COPA) 2017, p. 118-131, 2017

SNIC Science Cloud (SSC): A national-scale cloud infrastructure for Swedish academia

Toor, Salman; Lindberg, Mathias; Fällman, Ingemar; Vallin, Andreas et al.

Part of Proc. 13th International Conference on e-Science, p. 219-227, 2017

• DOI for SNIC Science Cloud (SSC): A national-scale cloud infrastructure for Swedish academia

Conformal prediction in Spark: Large-scale machine learning with confidence

Capuccini, Marco; Carlsson, Lars; Norinder, Ulf; Spjuth, Ola

Part of Proc. 2nd International Symposium on Big Data Computing, p. 61-67, 2015

• DOI for Conformal prediction in Spark: Large-scale machine learning with confidence

Interpretation of Conformal Prediction Classification Models

Ahlberg, Ernst; Spjuth, Ola; Hasselgren, Catrin; Carlsson, Lars

Part of STATISTICAL LEARNING AND DATA SCIENCES, p. 323-334, 2015

• DOI for Interpretation of Conformal Prediction Classification Models

HTSeq-Hadoop: Extending HTSeq for Massively Parallel Sequencing Data Analysis using Hadoop

Siretskiy, Alexey; Spjuth, Ola

Part of Proc. 10th International Conference on e-Science, p. 317-323, 2014

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NGS data management and analysis for hundreds of projects: Experiences from Sweden

Spjuth, Ola

Part of NGS Data after the Gold Rush, 2013

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Synergy Conformal Prediction for Regression

Gauraha, Niharika; Spjuth, Ola

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Robust Knowledge Transfer in Learning Under Privileged Information Framework

Gauraha, Niharika; Söderdahl, Fabian; Spjuth, Ola

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A biochemical signature of progressive multiple sclerosis

Herman, Stephanie; Emami Khoonsari, Payam; Bergman, Joakim; Svenningsson, Anders et al.

Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud

Moreno, Pablo; Pireddu, Luca; Roger, Pierrick; Goonasekera, Nuwan et al.

• DOI for Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud

Exploring the evolution of cellular morphological changes after drug administration based on brightfield image data

Harrison, Philip J.; Rietdijk, Jonne; Holmberg, David; Carreras-Puigvert, Jordi et al.

AROS: Open Source Lab Automation Enables Fully Automated CellPainting

Dahlö, Martin; Larsson, Anders; Rosén, Dan; Francisco Rodríguez, María Andreína et al.

Pharmaceutical Bioinformatics Primer

Spjuth, Ola

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