TY - JOUR
T1 - Domains, motifs and clusters in the protein universe
AU - Liu, Jinfeng
AU - Rost, Burkhard
N1 - Funding Information:
Thanks to Henry Bigelow (Columbia University) for helpful comments and for critical proofreading. JL and BR were supported by the grants 1-P50-GM62413-01 and RO1-GM63029-01 from the National Institutes of Health (NIH). Last, but not least, thanks to all those who deposit their experimental data in public databases, and to those who maintain these databases.
PY - 2003/2
Y1 - 2003/2
N2 - The rapid growth of bio-sequence information has resulted in an increasing demand for reliable methods that group proteins. A few databases with curated alignments of protein families have demonstrated that expert-driven repositories can keep up with the data deluge in the genome era. These original resources implicitly identify domain-like modules in proteins. An increasing number of automatic methods have sprouted over the past few years that cluster the protein universe. Many of these implicitly dissect proteins into structural domain-like fragments. In a very coarse-grained evaluation, some of the automatic methods appear to be on par with expert-driven approaches. However, neither automatic nor manual methods are currently entirely up to the challenges of tasks such as target selection in structural genomics. Thus, we urgently need refined and sustained automatic clustering tools.
AB - The rapid growth of bio-sequence information has resulted in an increasing demand for reliable methods that group proteins. A few databases with curated alignments of protein families have demonstrated that expert-driven repositories can keep up with the data deluge in the genome era. These original resources implicitly identify domain-like modules in proteins. An increasing number of automatic methods have sprouted over the past few years that cluster the protein universe. Many of these implicitly dissect proteins into structural domain-like fragments. In a very coarse-grained evaluation, some of the automatic methods appear to be on par with expert-driven approaches. However, neither automatic nor manual methods are currently entirely up to the challenges of tasks such as target selection in structural genomics. Thus, we urgently need refined and sustained automatic clustering tools.
UR - http://www.scopus.com/inward/record.url?scp=0037305939&partnerID=8YFLogxK
U2 - 10.1016/S1367-5931(02)00003-0
DO - 10.1016/S1367-5931(02)00003-0
M3 - Review article
C2 - 12547420
AN - SCOPUS:0037305939
SN - 1367-5931
VL - 7
SP - 5
EP - 11
JO - Current Opinion in Chemical Biology
JF - Current Opinion in Chemical Biology
IS - 1
ER -