Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Karthik Muthukumar"'
Autor:
Daniel E. Almonacid, Shreyas V. Kumbhare, Patricia Francis-Lyon, Dashyanng Kachru, Tejaswini Uday, Carmel Irudayanathan, Karthik Muthukumar, Roshni Ricchetti, Simitha Singh-Rambiritch, Juan Ugalde, Parambir Dulai, Ranjan Sinha
Publikováno v:
Gastroenterology. 162:S-1010
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::017b861832d2ad0fa742824095203003
https://doi.org/10.1016/s0016-5085(22)62398-9
https://doi.org/10.1016/s0016-5085(22)62398-9
Autor:
Roshni Ray Ricchetti, Ranjan Sinha, Karthik Muthukumar, Simitha Singh-Rambiritch, Bruce Underwood, Imran Junaid, Chandana Reddy-Sinha, Jessica Kotini, Carmel Irudayanathan
Background: Obesity is a multifactorial disease with a complex pathogenesis and several prevalent and debilitating associated comorbidities. New genome and microbiome based diagnostic and therapeutic strategies (i.e., personalized medicine) are incre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::eb7caa919dd314da2a8ac04f015f4d4f
https://zenodo.org/record/7932598
https://zenodo.org/record/7932598
Autor:
Mei Mei Chang, Yu Guo, Anders Jacobsen Skanderup, Karthik Muthukumar, Weitai Huang, Probhonjon Baruah
Publikováno v:
Bioinformatics
Summary Somatic Mutation calling method using a Random Forest (SMuRF) integrates predictions and auxiliary features from multiple somatic mutation callers using a supervised machine learning approach. SMuRF is trained on community-curated matched tum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7728ba6f7874080b082a7367ccabff52
https://doi.org/10.1093/bioinformatics/btz018
https://doi.org/10.1093/bioinformatics/btz018
Autor:
Mei Mei Chang, Probhonjon Baruah, Weitai Huang, Yu Guo, Anders Jacobsen Skanderup, Karthik Muthukumar
ABSTARCTSummarySMuRF is an ensemble method for prediction of somatic point mutations (SNVs) and small insertions/deletions (indels) in cancer genomes. The method integrates predictions and auxiliary features from different somatic mutation callers us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42f03f93c177130a1d80b682950e0260
https://doi.org/10.1101/270413
https://doi.org/10.1101/270413
Autor:
Huang, Weitai, Guo, Yu Amanda, Muthukumar, Karthik, Baruah, Probhonjon, Chang, Mei Mei, Skanderup, Anders Jacobsen
Publikováno v:
Bioinformatics; Sep2019, Vol. 35 Issue 17, p3157-3159, 3p