Source: PLoS Computational Biology, Vol 17, Iss 5, p e1008765 (2021)Dias Louro, Marco António; Bettencourt-Dias, Mónica; Bank, Claudia (2021). Patterns of selection

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Assessing the contribution of tumor mutational phenotypes to cancer progression risk

Authors : Ziyi Cui; Jesse Eaton; Russell Schwartz

Subjects: 0301 basic medicine; Epidemiology; Somatic evolution in cancer

Source: PLoS Computational Biology, Vol 17, Iss 3, p e1008777 (2021)PLoS Computational Biology

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Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer

Authors : Chloé-Agathe Azencott; Héctor Climente-González; Christine Lonjou

Subjects: Proteomics; 0301 basic medicine; Epidemiology

Source: PLoS Computational Biology, Vol 17, Iss 3, p e1008819 (2021)PLoS Computational Biology

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Predicting therapeutic drugs for hepatocellular carcinoma based on tissue-specific pathways

Authors : Xiangzhi Li; Fei Xie; Yang Yang

Subjects: 0301 basic medicine; Oncology; Databases, Factual

Source: PLoS Computational Biology, Vol 17, Iss 2, p e1008696 (2021)PLoS Computational Biology

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Signatures of neutral evolution in exponentially growing tumors: A theoretical perspective

Authors : Rick Durrett; Hwai-Ray Tung

Subjects: 0301 basic medicine; Carcinogenesis; Normal Distribution

Source: PLoS Computational BiologyPLoS Computational Biology, Vol 17, Iss 2, p e1008701 (2021)

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The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy

Authors : Kristina M. Kruglyak; Mahdi Golkaram; Sven Bilke

Subjects: 0301 basic medicine; Oncology; Male

Source: PLoS Computational BiologyPLoS Computational Biology, Vol 16, Iss 11, p e1008332 (2020)

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Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy

Authors : Divya Venkat; Natacha Comandante-Lou; Mohan Manikkam

Subjects: 0301 basic medicine; Cancer drugs; Drug action

Source: PLoS Computational Biology, Vol 16, Iss 2, p e1007688 (2020)PLoS Computational Biology

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Individualized genetic network analysis reveals new therapeutic vulnerabilities in 6,700 cancer genomes

Authors : Yadi Zhou; Feixiong Cheng; Junfei Zhao

Subjects: 0301 basic medicine; Epidemiology; Carcinogenesis

Source: PLoS Computational BiologyPLoS Computational Biology, Vol 16, Iss 2, p e1007701 (2020)

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نتائج البحث

فلترة النتائج

Modeling historic incidence trends implies early field cancerization in esophageal squamous cell carcinoma

Efficient representations of tumor diversity with paired DNA-RNA aberrations

Patterns of selection against centrosome amplification in human cell lines

Assessing the contribution of tumor mutational phenotypes to cancer progression risk

Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer

Predicting therapeutic drugs for hepatocellular carcinoma based on tissue-specific pathways

Signatures of neutral evolution in exponentially growing tumors: A theoretical perspective

The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy

Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy

Individualized genetic network analysis reveals new therapeutic vulnerabilities in 6,700 cancer genomes

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