Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Samson H. Fong"'
Autor:
Kyle Ford, Brenton P. Munson, Samson H. Fong, Rebecca Panwala, Wai Keung Chu, Joseph Rainaldi, Nongluk Plongthongkum, Vinayagam Arunachalam, Jarek Kostrowicki, Dario Meluzzi, Jason F. Kreisberg, Kristen Jensen-Pergakes, Todd VanArsdale, Thomas Paul, Pablo Tamayo, Kun Zhang, Jadwiga Bienkowska, Prashant Mali, Trey Ideker
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-20 (2023)
Abstract Cell-cycle control is accomplished by cyclin-dependent kinases (CDKs), motivating extensive research into CDK targeting small-molecule drugs as cancer therapeutics. Here we use combinatorial CRISPR/Cas9 perturbations to uncover an extensive
Externí odkaz:
https://doaj.org/article/fcd5b895626948aba19a440f77fb4bf1
Autor:
Daniel E. Carlin, Samson H. Fong, Yue Qin, Tongqiu Jia, Justin K. Huang, Bokan Bao, Chao Zhang, Trey Ideker
Publikováno v:
iScience, Vol 16, Iss , Pp 155-161 (2019)
Summary: We present an accessible, fast, and customizable network propagation system for pathway boosting and interpretation of genome-wide association studies. This system—NAGA (Network Assisted Genomic Association)—taps the NDEx biological netw
Externí odkaz:
https://doaj.org/article/533f3d426cf940c08329d1bed37286a1
Publikováno v:
Cancer research. 81(24)
Oncogenesis relies on the alteration of multiple driver genes, but precisely which groups of alterations lead to cancer is not well understood. To chart these combinations, Zhao and colleagues use the CRISPR-Cas9 system to knockout all pairwise combi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b80f22539ebda7b0219b87442b040178
https://pubmed.ncbi.nlm.nih.gov/34561273
https://pubmed.ncbi.nlm.nih.gov/34561273
Autor:
Samson H. Fong, Daniel E. Carlin, Kivilcim Ozturk, Trey Ideker, Nadia Arang, Bokan Bao, Hunter Bennett, Xiaochun Cai, Kevin Chau, Bethany Fixsen, Edahi Gonzalez-Avalos, Alexander Hakansson, Vincent Hu, Arya Kaul, Irina Kufareva, Duong Nguyen, Elly Poretsky, Yue Qin, David Rideout, Isaac Shamie, Alex Sharp, Erica Silva, James Sorrentino, Anya Umlauf, Chao Zhang, Jessica Zhou
Publikováno v:
Cell systems. 8(4)
Biological networks can substantially boost power to identify disease genes in genome-wide association studies. To explore different network GWAS methods, we challenged students of a UC San Diego graduate level bioinformatics course, Network Biology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06157fc31fec327176fd4f141f0e81b3
https://pubmed.ncbi.nlm.nih.gov/31647918
https://pubmed.ncbi.nlm.nih.gov/31647918