Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Sinha, Saurabh"'
Autor:
Tompa M; Department of Computer Science and Engineering, Box 352350, University of Washington, Seattle, Washington 98195-2350, USA. tompa@cs.washington.edu, Li N, Bailey TL, Church GM, De Moor B, Eskin E, Favorov AV, Frith MC, Fu Y, Kent WJ, Makeev VJ, Mironov AA, Noble WS, Pavesi G, Pesole G, Régnier M, Simonis N, Sinha S, Thijs G, van Helden J, Vandenbogaert M, Weng Z, Workman C, Ye C, Zhu Z
Publikováno v:
Nature biotechnology [Nat Biotechnol] 2005 Jan; Vol. 23 (1), pp. 137-44.
Autor:
Xie, Xiaoman1 (AUTHOR), Sinha, Saurabh2,3 (AUTHOR) saurabh.sinha@bme.gatech.edu
Publikováno v:
PLoS Computational Biology. 6/5/2024, Vol. 20 Issue 6, p1-31. 31p.
Autor:
Emad, Amin1 amin.emad@mcgill.ca, Sinha, Saurabh2,3,4 sinhas@illinois.edu
Publikováno v:
NPJ Systems Biology & Applications. 2/8/2021, Vol. 7 Issue 1, p1-14. 14p.
Publikováno v:
Proceedings: Biological Sciences, 2012 Dec . 279(1749), 4929-4938.
Externí odkaz:
https://www.jstor.org/stable/41727769
Autor:
Khajouei, Farzaneh1, Sinha, Saurabh1,2 sinhas@illinois.edu
Publikováno v:
PLoS Computational Biology. 9/26/2018, Vol. 14 Issue 9, p1-24. 24p. 1 Chart, 4 Graphs.
Autor:
Alaux, Cédric, Sinha, Saurabh, Hasadsri, Linda, Hunt, Greg J., Guzmán-Novoa, Ernesto, DeGrandi-Hoffman, Gloria, Uribe-Rubio, José Luis, Southey, Bruce R., Rodriguez-Zas, Sandra, Robinson, Gene E.
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2009 Sep 01. 106(36), 15400-15405.
Externí odkaz:
https://www.jstor.org/stable/40484724
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2006 Oct . 103(44), 16352-16357.
Externí odkaz:
https://www.jstor.org/stable/30052162
Autor:
Seward, Christopher H., Saul, Michael C., Troy, Joseph M., Dibaeinia, Payam, Zhang, Huimin, Sinha, Saurabh, Stubbs, Lisa J.
Publikováno v:
PLoS ONE; 2/22/2022, Vol. 17 Issue 2, p1-22, 22p
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 1, p e1007607 (2020)
PLoS Computational Biology
PLoS Computational Biology
Prediction of clinical drug response (CDR) of cancer patients, based on their clinical and molecular profiles obtained prior to administration of the drug, can play a significant role in individualized medicine. Machine learning models have the poten
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64864dc66b0ba3e8a2fa57037b3df33f
Autor:
Samee, Md. Abul Hassan1 samee1@illinois.edu, Sinha, Saurabh1,2 sinhas@illinois.edu
Publikováno v:
PLoS Computational Biology. Mar2014, Vol. 10 Issue 3, p1-21. 21p. 3 Diagrams, 6 Graphs.