Text mining for biology--the way forward: opinions from leading scientists.
This article collects opinions from leading scientists about how text mining can provide better access to the biological literature, how the scientific community can help with this process, what the next steps are, and what role future BioCreative evaluations can play. The responses identify several broad themes, including the possibility of fusing literature and biological databases through text mining; the need for user interfaces tailored to different classes of users and supporting community-based annotation; the importance of scaling text mining technology and inserting it into larger workflows; and suggestions for additional challenge evaluations, new applications, and additional resources needed to make progress.
Altman
Russ B
RB
Stanford University, Stanford, California, 94305-5444, USA.
Bergman
Casey M
CM
Blake
Judith
J
Blaschke
Christian
C
Cohen
Aaron
A
Gannon
Frank
F
Grivell
Les
L
Hahn
Udo
U
Hersh
William
W
Hirschman
Lynette
L
Jensen
Lars Juhl
LJ
Krallinger
Martin
M
Mons
Barend
B
O'Donoghue
Seán I
SI
Peitsch
Manuel C
MC
Rebholz-Schuhmann
Dietrich
D
Shatkay
Hagit
H
Valencia
Alfonso
A
D019295:Computational Biology / Q000379:methods*; D005104:Expert Testimony; D011643:Publishing