Transcriptional pathway signatures predict MEK addiction and response to selumetinib (AZD6244)

Dry JR, Pavey S, Pratilas CA, Harbron C, Runswick S, Hodgson D, Chresta C, McCormack R, Byrne N, Cockerill M, Graham A, Beran G, Cassidy A, Haggerty C, Brown H, Ellison G, Dering J, Taylor BS, Stark M, Bonazzi V, Ravishankar S, Packer L, Xing F, Solit DB, Finn RS, Rosen N, Hayward NK, French T, Smith PD.

Cancer Res. 2010 Mar 15; 70(6):2264-73

PMID: 20215513

Identifying and classifying biomedical perturbations in text

Rodriguez-Esteban R, Roberts PM, Crawford ME.

Nucleic Acids Res. 2009 Feb; 37(3):771-7

PMID: 19074486

The CALBC Silver Standard Corpus - Harmonizing multiple semantic annotations in a large biomedical corpus

Rebholz-Schuhmann D, Jimeno Yepes AJ, Van Mulligen EM, Kang N, Kors J, Milward D, Corbett P, Hahn U.

Proc 3rd Int Symp Languages Biology Medicine. 2009 Nov; pp64-72


Mining protein-protein interactions from published literature using Linguamatics I2E

Bandy J, Milward D, McQuay S.

Methods Mol Biol. 2009; 563:3-13

PMID: 19597777


Natural language processing (NLP) technology can be used to rapidly extract protein-protein interactions from large collections of published literature. In this chapter we will work through a case study using MEDLINE biomedical abstracts (1) to find how a specific set of 50 genes interact with each other.

Information needs and the role of text mining in drug development

Roberts PM, Hayes WS.

Pac Symp Biocomput. 2008:pp592-603

PMID: 18229718


Drug development generates information needs from groups throughout a company. Knowing where to look for high-quality information is essential for minimizing costs and remaining competitive.