A Novel Pathway Analysis Approach Based on the Unexplained Disregulation of Genes

Autor: Sahar Ansari, Michele Donato, Sorin Draghici, Rebecca Tagett, Calin Voichita

Publikováno v: Proceedings of the IEEE. :1-14

A crucial step in the understanding of any phenotype is the correct identification of the signaling pathways that are significantly impacted in that phenotype. However, most current pathway analysis methods produce both false positives as well as fal

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8527c69e6dd4ef4e856af552669bfd2c
https://doi.org/10.1109/jproc.2016.2531000

Serum prognostic biomarkers in head and neck cancer patients

Autor: Adam J. Folbe, Harvinder Talwar, Michael A. Tainsky, Calin Voichita, Seema Sethi, George H. Yoo, Wei Chen, Fauzia Siddiq, Andrew M. Fribley, Gerald Jeyapalan, Sorin Draghici, Madhumita Chatterjee, Ammar Sukari, Ho-Sheng Lin, Harold Kim

Publikováno v: The Laryngoscope. 124(8)

Objectives/Hypothesis: A reliable estimate of survival is important as it may impact treatment choice. The objective of this study is to identify serum autoantibody biomarkers that can be used to improve prognostication for patients affected with hea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06f0d58627be4bcd842050a7e7de66aa
https://pubmed.ncbi.nlm.nih.gov/24347532

Strengths and limitations of microarray-based phenotype prediction: Lessons learned from the IMPROVER Diagnostic Signature Challenge

Autor: Tarca, Al, Lauria, M, Unger, M, Bilal, E, Boue, S, Kumar Dey, K, Hoeng, J, Koeppl, H, Martin, F, Meyer, P, Nandy, P, Norel, R, Peitsch, M, Rice, Jj, Romero, R, Stolovitzky, G, Talikka, M, Xiang, Y, Zechner, C, IMPROVER DSC Collaborators: Alan Veliz Cuba, Joe, Song, Hien, Nguyen, Michael, Zeller, Peter, Sadowski, Steffen, Klamt, Sandra, Heise, Mika, Gustafsson, Alberto, Malovini, Francesca, Mulas, Nicola, Barbarini, Michael, Unger, Preetam, Nandy, Kushal Kumar Dey, Christoph, Zechner, Heinz, Koeppl, Nicoleta, Cristea, Tom, Petty, Liu, Yi, Tiffany Ting Liu, Cheng, Zhao, Giovanni, Felici, Mario, Lauria, Paolo, Provero, Tabak, Esteban G., Benjamin Haibe Kains, Simon Papillion Cavanagh, Nicolas De Jay, Rene, Dreos, Fengfeng, Zhou, Weixiong, Zhang, Zheng, Chen, Yuxuan, Hu, Kenny, Chau, de Almeida, Rita M. C., da Silva, Samoel R. M., Gabriel Cury Perrone, David, Rossell, Patrick, Aloy, Mei lyn Ong, Calin, Voichita, Saied, Haidarian, Rebecca, Tagett, Lydia, Hopp, Bo, Li, Bhattacharjee, M., Jian lei Gu, Meena, Choi, Christopher, Poirel, David, Badger, Ahsanur, Rahman, Richard, Rodrigues, Nikolay, Balov, Maria, Chikina, Elena, Zaslavsky, Tarca, Adi L., Roberto, Romero, Xianwen, Ren, Steve, Horvath, Lin, Song, Sol, Efroni, Rotem Ben Hamo, Mayte Suarez Farinas, Suyan, Tian, Seunghak, Lee, Wei Keat Lim, Xiaoping, Liu, Luonan, Chen, Tao, Zeng, Huang, Di, Inchi, Hu, mer Sinan Sarac, A., Torik, Ayoubi, Kai, Wang, Hooncho, Ji, Alan, Lin, Chao, Ye, Junfeng, Li, Hongfei, Cui, Peter, Salzman, Marko Sysi Aho, Sandra Castillo Priego, Matej, Oresic, Gopal, Peddinti, DI CAMILLO, Barbara, Zeke, Maier, Zhenshu, Wen, Xin dong Zhang

Publikováno v: Bioinformatics, 29 (22)

Bioinformatics, 29 (22)
ISSN:1367-4803
ISSN:1460-2059

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb6dc156c050dda32378da59237f5e8b

Identifying uncertainty regions in Support Vector Machines using geometric margin and convex hulls

Autor: Calin Voichita, Purvesh Khatri, Sorin Draghici

Publikováno v: IJCNN

Like most classification techniques, the existing support vector machines (SVM) approaches are challenged to correctly classify their input when the data points are either very close to the decision boundary or very dissimilar from the training data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6337b294e4ac73c32ea3bf3dbd1046b4
https://doi.org/10.1109/ijcnn.2008.4634269