Sara Younes

Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Yones, Sara A.; Annett, Alva; Stoll, Patricia; Diamanti, Klev et al.

Part of Scientific Reports, 2022

• DOI for Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment

Garbulowski, Mateusz; Smolinska Garbulowska, Karolina; Cabuk, Ugur; Younes, Sara et al.

Part of Cancers, 2022

• DOI for Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment
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Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression

Stratmann, Svea; Yones, Sara A.; Garbulowski, Mateusz; Sun, Jitong et al.

Part of Blood Advances, p. 152-164, 2022

• DOI for Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression
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Uncovering biomarkers and molecular heterogeneity of complex diseases: Utilizing the power of Data Science

Younes, Sara

2021

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Supplementary material: Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Yones, Sara A.; Annett, Alva; Stoll, Patricia; Diamanti, Klev et al.

2021

• Download full text (pdf) of Supplementary material: Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Yones, Sara A.; Annett, Alva; Stoll, Patricia; Diamanti, Klev et al.

Part of Scientific Reports, 2022

• DOI for Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment

Garbulowski, Mateusz; Smolinska Garbulowska, Karolina; Cabuk, Ugur; Younes, Sara et al.

Part of Cancers, 2022

• DOI for Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment
• Download full text (pdf) of Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment

Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression

Stratmann, Svea; Yones, Sara A.; Garbulowski, Mateusz; Sun, Jitong et al.

Part of Blood Advances, p. 152-164, 2022

• DOI for Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression
• Download full text (pdf) of Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression

MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data

Yones, Sara A.; Csombordi, Rajmund; Komorowski, Jan; Diamanti, Klev

Part of Metabolites, 2021

• DOI for MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data
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What Is Abnormal in Normal Karyotype Acute Myeloid Leukemia in Children?: Analysis of the Mutational Landscape and Prognosis of the TARGET-AML Cohort

Herlin, Morten Krogh; Yones, Sara A.; Kjeldsen, Eigil; Holmfeldt, Linda et al.

Part of Genes, 2021

• DOI for What Is Abnormal in Normal Karyotype Acute Myeloid Leukemia in Children?: Analysis of the Mutational Landscape and Prognosis of the TARGET-AML Cohort
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Genomic characterization of relapsed acute myeloid leukemia reveals novel putative therapeutic targets

Stratmann, Svea; Yones, Sara A.; Mayrhofer, Markus; Norgren, Nina et al.

Part of Blood Advances, p. 900-912, 2021

• DOI for Genomic characterization of relapsed acute myeloid leukemia reveals novel putative therapeutic targets

Uncovering biomarkers and molecular heterogeneity of complex diseases: Utilizing the power of Data Science

Younes, Sara

2021

• Download full text (pdf) of Uncovering biomarkers and molecular heterogeneity of complex diseases: Utilizing the power of Data Science

Supplementary material: Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Yones, Sara A.; Annett, Alva; Stoll, Patricia; Diamanti, Klev et al.

2021

• Download full text (pdf) of Supplementary material: Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

SUPPLEMENTARY MATERIAL: Transcriptomic analysis reveals pro-inflammatory signatures associated with acute myeloid leukemia progression

Stratmann, Svea; Yones, Sara A.; Garbulowski, Mateusz; Sun, Jitong et al.

2021

Supplementary tables:MetaFetcheR: An R package for complete mapping of small compound data

Yones, Sara A.; Csombordi, Rajmund; Komorowski, Jan; Diamanti, Klev

2021

• Download full text (pdf) of Supplementary tables:MetaFetcheR: An R package for complete mapping of small compound data

SUPPLEMENTARY MATERIAL: Machine learning-based analysis of glioma grades reveals co-enrichment

Garbulowski, Mateusz; Smolinska Garbulowska, Karolina; Çabuk, Uğur; Yones, Sara A. et al.

2021

SUPPLEMENTAL INFORMATION FOR: Transcriptomic analysis reveals pro-inflammatory signatures associated with acute myeloid leukemia progression

Stratmann, Svea; Yones, Sara A.; Garbulowski, Mateusz; Sun, Jitong et al.

2020

• Download full text (pdf) of SUPPLEMENTAL INFORMATION FOR: Transcriptomic analysis reveals pro-inflammatory signatures associated with acute myeloid leukemia progression