M
Michal Krassowski
Researcher at Ontario Institute for Cancer Research
Publications - 14
Citations - 846
Michal Krassowski is an academic researcher from Ontario Institute for Cancer Research. The author has contributed to research in topics: Medicine & Endometriosis. The author has an hindex of 5, co-authored 8 publications receiving 471 citations. Previous affiliations of Michal Krassowski include University of Oxford & University of Warsaw.
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Journal ArticleDOI
Pathogenic Germline Variants in 10,389 Adult Cancers
Kuan-lin Huang,R. Jay Mashl,Yige Wu,Deborah I. Ritter,Jiayin Wang,Clara Oh,Marta Paczkowska,Sheila Reynolds,Matthew A. Wyczalkowski,Ninad Oak,Adam D. Scott,Michal Krassowski,Andrew D. Cherniack,Kathleen E. Houlahan,Reyka G Jayasinghe,Liang-Bo Wang,Daniel Cui Zhou,Di Liu,Song Cao,Young Won Kim,Amanda Koire,Joshua F. McMichael,Vishwanathan Hucthagowder,Tae-Beom Kim,Abigail Hahn,Chen Wang,Michael D. McLellan,Fahd Al-Mulla,Kimberly J. Johnson,Olivier Lichtarge,Paul C. Boutros,Paul C. Boutros,Benjamin J. Raphael,Alexander J. Lazar,Wei Zhang,Michael C. Wendl,Ramaswamy Govindan,Sanjay Jain,David A. Wheeler,Shashikant Kulkarni,John F. DiPersio,Jüri Reimand,Jüri Reimand,Funda Meric-Bernstam,Ken Chen,Ilya Shmulevich,Sharon E. Plon,Feng Chen,Li Ding +48 more
TL;DR: The largest investigation of predisposition variants in cancer to date finds 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types, informing future guidelines of variant classification and germline genetic testing in cancer.
Journal ArticleDOI
State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing.
TL;DR: This review provides guidance to interested users of the multi-omics domain by addressing challenges of the underlying biology, giving an overview of the available toolset, addressing common pitfalls, and acknowledging current methods’ limitations.
Journal ArticleDOI
ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins.
Michal Krassowski,Michal Krassowski,Marta Paczkowska,Kim Cullion,Tina Huang,Irakli Dzneladze,Irakli Dzneladze,B. F. Francis Ouellette,B. F. Francis Ouellette,Joseph Tadashi Yamada,Amélie Fradet-Turcotte,Jüri Reimand,Jüri Reimand +12 more
TL;DR: Interpretation of genetic variation is needed for deciphering genotype-phenotype associations, mechanisms of inherited disease, and cancer driver mutations, and ActiveDriverDB is a comprehensive human proteo-genomics database that annotates disease mutations and population variants through the lens of PTMs.
Journal ArticleDOI
Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks.
Helen He Zhu,Helen He Zhu,Liis Uusküla-Reimand,Keren Isaev,Keren Isaev,Lina Wadi,Azad Alizada,Shimin Shuai,Shimin Shuai,Vincent Huang,Dike Aduluso-Nwaobasi,Marta Paczkowska,Diala Abd-Rabbo,Oliver Ocsenas,Oliver Ocsenas,Minggao Liang,J. Drew Thompson,Yao Li,Luyao Ruan,Michal Krassowski,Irakli Dzneladze,Jared T. Simpson,Jared T. Simpson,Mathieu Lupien,Mathieu Lupien,Lincoln D. Stein,Lincoln D. Stein,Paul C. Boutros,Michael D. Wilson,Jüri Reimand,Jüri Reimand +30 more
TL;DR: A driver discovery method is developed and analyzed 120,788 cis-regulatory modules (CRMs) across 1,844 whole tumor genomes from the ICGC-TCGA PCAWG project, finding 30 CRMs with enriched SNVs and indels (FDR < 0.05).
Posted ContentDOI
Candidate cancer driver mutations in superenhancers and long-range chromatin interaction networks
Lina Wadi,Liis Uusküla-Reimand,Keren Isaev,Shimin Shuai,Huang,Minggao Liang,J. Drew Thompson,Yao Li,Luyao Ruan,Marta Paczkowska,Michal Krassowski,Irakli Dzneladze,Ken Kron,Alex Murison,Parisa Mazrooei,Robert G. Bristow,Jared T. Simpson,Mathieu Lupien,Wilson,Lincoln D. Stein,Paul C. Boutros,Jüri Reimand +21 more
TL;DR: This study analyzed 150,000 cis-regulatory regions in 1,844 whole cancer genomes from the ICGC-TCGA PCAWG project and found 41 frequently mutated regulatory elements (FMREs) enriched in non-coding SNVs and indels (FDR<0.05) characterized by aging-associated mutation signatures and frequent structural variants.