A comprehensive benchmark of kernel methods to extract protein-protein interactions from literature.

Autor: Domonkos Tikk, Philippe Thomas, Peter Palaga, Jörg Hakenberg, Ulf Leser

Publikováno v: PLoS Computational Biology, Vol 6, p e1000837 (2010)

The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein-protein interactions (PPIs) reported in scientific publications is one of the core topics of text mining in the life sciences. Re

Externí odkaz: https://doaj.org/article/162c1482002241ca9c9557d4882ff2f8

Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer

Autor: Eric J. Small, Lawrence Fong, Karen E. Knudsen, Brad Sickler, Robert E. Reiter, Charles J. Ryan, Theodore C. Goldstein, Tomasz M. Beer, Martin E. Gleave, Rahul Aggarwal, Julian S. Gehring, Rajdeep Das, John Shon, Scott M. Dehm, Alan Ashworth, David A. Quigley, Ha X. Dang, Terence W. Friedlander, R. Keira Cheetham, Denise Playdle, Paul Lloyd, Serafim Batzoglou, Jack F. Youngren, Jin Zhang, Nathan A. Lack, Adam Foye, Felix Y. Feng, Jörg Hakenberg, Adina M. Bailey, Owen N. Witte, Abhijit Parolia, Scott A. Tomlins, Travis J. Barnard, Donavan T. Cheng, Jiaoti Huang, Li Zhang, P. G. Febbo, Alexander W. Wyatt, Kim N. Chi, Matthew Rettig, Vishal Kothari, Daniel E. Spratt, Housheng Hansen He, Haolong Li, George Thomas, Arnold Liao, Shuang G. Zhao, Hui Li, Joshua M. Stuart, Won Kim, Primo N. Lara, Christopher G. Maher, Jonathan Chou, Joshi J. Alumkal, Amina Zoubeidi, Marc D. Perry, Ruhollah Moussavi-Baygi, Luke A. Gilbert, Arul M. Chinnaiyan, Christopher P. Evans, Hani Goodarzi, Marcin Cieslik, Kyle Kai-How Farh

Publikováno v: Cell, vol 174, iss 3
Quigley, DA; Dang, HX; Zhao, SG; Lloyd, P; Aggarwal, R; Alumkal, JJ; et al.(2018). Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer. Cell, 174(3), 758-769.e9. doi: 10.1016/j.cell.2018.06.039. UC Davis: Retrieved from: http://www.escholarship.org/uc/item/796124qb

© 2018 Elsevier Inc. While mutations affecting protein-coding regions have been examined across many cancers, structural variants at the genome-wide level are still poorly defined. Through integrative deep whole-genome and -transcriptome analysis of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1928a409b1341bcafb393804416865b5
https://escholarship.org/uc/item/796124qb

Author Correction: Predicting the clinical impact of human mutation with deep neural networks

Autor: John Shon, Kyle Kai-How Farh, Xiaolin Li, Serafim Batzoglou, Yanjun Li, Hong Gao, Jeremy F. McRae, Jörg Hakenberg, Laksshman Sundaram, Nondas Fritzilas, Samskruthi Reddy Padigepati, Jinbo Xu, Jack A. Kosmicki, Anindita Dutta

Publikováno v: Nature genetics

Millions of human genomes and exomes have been sequenced, but their clinical applications remain limited due to the difficulty of distinguishing disease-causing mutations from benign genetic variation. Here we demonstrate that common missense variant

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32209a9b35cce3ba7f6a062bcb1595b4
https://doi.org/10.1038/s41588-018-0329-z

Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks

Autor: Kristin L. Ayers, Benjamin S. Glicksberg, Roman Kosoy, Rong Chen, Meng Ma, Li Li, Khader Shameer, Marcus A. Badgeley, Gabriel E. Hoffman, Joel T. Dudley, Jörg Hakenberg, Eric E. Schadt, Shuyu Dan Li, Nam Pho, Noam D. Beckmann, Chirag J. Patel

Publikováno v: Bioinformatics

Motivation: Underrepresentation of racial groups represents an important challenge and major gap in phenomics research. Most of the current human phenomics research is based primarily on European populations; hence it is an important challenge to exp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed9ccada7c9e48c93bbf14af6d8cfa3a
https://pubmed.ncbi.nlm.nih.gov/27307606

Incremental Information Extraction Using Relational Databases

Autor: Phan Huy Tu, Luis Tari, Jörg Hakenberg, Tran Cao Son, Chitta Baral, Yi Chen, Graciela Gonzalez

Publikováno v: IEEE Transactions on Knowledge and Data Engineering. 24:86-99

Information extraction systems are traditionally implemented as a pipeline of special-purpose processing modules targeting the extraction of a particular kind of information. A major drawback of such an approach is that whenever a new extraction goal

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8507f33e55d9de894ae7f7d4d50ef4a4
https://doi.org/10.1109/tkde.2010.214