Understanding Protein Function on a Genome-scale using Networks
The Future of Scientific Publishing: Mining Publications to Study the Structure
of Science
My talk will focus on a vision for Scientific Publishing: How we could
potentially mine all the information in publications, to glean new scientific
facts and to study the structure of science itself. I'll provide some
illustrations of the latter. I will also talk about some impediments to
realizing this vision and potential solutions.
Mark Gerstein
Yale University
Open access: taking full advantage of the content.
PE Bourne, JL Fink, M Gerstein (2008) PLoS Comput Biol 4: e1000037.
Uncovering trends in gene naming.
MR Seringhaus, PD Cayting, MB Gerstein (2008) Genome Biol 9: 401.
Structured digital abstract makes text mining easy.
M Gerstein, M Seringhaus, S Fields (2007) Nature 447: 142.
RNAi development.
M Gerstein, SM Douglas (2007) PLoS Comput Biol 3: e80.
Chemistry Nobel rich in structure.
M Seringhaus, M Gerstein (2007) Science 315: 40-1.
Data mining on the web.
A Smith, M Gerstein (2006) Science 314: 1682; author reply 1682.
Tools needed to navigate landscape of the genome.
M Gerstein (2006) Nature 440: 740.
PubNet: a flexible system for visualizing literature derived networks.
SM Douglas, GT Montelione, M Gerstein (2005) Genome Biol 6: R80.
Annotation of the human genome.
M Gerstein (2000) Science 288: 1590.
E-publishing on the Web: promises, pitfalls, and payoffs for bioinformatics.
M Gerstein (1999) Bioinformatics 15: 429-31.
