PMID- 21689479
OWN - NLM
STAT- MEDLINE
DCOM- 20111012
LR  - 20211020
IS  - 1752-0509 (Electronic)
IS  - 1752-0509 (Linking)
VI  - 5 Suppl 1
IP  - Suppl 1
DP  - 2011 May 4
TI  - Regulatory link mapping between organisms.
PG  - S4
LID - 10.1186/1752-0509-5-S1-S4 [doi]
AB  - BACKGROUND: Identification of gene regulatory networks is useful in understanding 
      gene regulation in any organism. Some regulatory network information has already 
      been determined experimentally for model organisms, but much less has been 
      identified for non-model organisms, and the limited amount of gene expression 
      data available for non-model organisms makes inference of regulatory networks 
      difficult. RESULTS: This paper proposes a method to determine the regulatory 
      links that can be mapped from a model to a non-model organism. Mapping a 
      regulatory network involves mapping the transcription factors and target genes 
      from one genome to another. In the proposed method, Basic Local Alignment Search 
      Tool (BLAST) and InterProScan are used to map the transcription factors, whereas 
      BLAST along with transcription factor binding site motifs and the GALF-P tool are 
      used to map the target genes. Experiments are performed to map the regulatory 
      network data of S. cerevisiae to A. thaliana and analyze the results. Since 
      limited information is available about gene regulatory network links, gene 
      expression data is used to analyze results. A set of rules are defined on the 
      gene expression experiments to identify the predicted regulatory links that are 
      well supported. CONCLUSIONS: Combining transcription factors mapped using BLAST 
      and subfamily classification, together with target genes mapped using BLAST and 
      binding site motifs, produced the best regulatory link predictions. More than 
      two-thirds of these predicted regulatory links that were analyzed using gene 
      expression data have been verified as correctly mapped regulatory links in the 
      target genome.
FAU - Sharma, Rachita
AU  - Sharma R
AD  - Faculty of Computer Science, University of New Brunswick, Fredericton, NB, 
      Canada. rachita.sharma@unb.ca
FAU - Evans, Patricia A
AU  - Evans PA
FAU - Bhavsar, Virendrakumar C
AU  - Bhavsar VC
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20110504
PL  - England
TA  - BMC Syst Biol
JT  - BMC systems biology
JID - 101301827
RN  - 0 (Fungal Proteins)
RN  - 0 (Plant Proteins)
RN  - 0 (RNA-Binding Proteins)
RN  - 0 (Transcription Factors)
RN  - 0 (p67 protein, Raphanus sativus)
SB  - IM
MH  - Arabidopsis/genetics/metabolism
MH  - Binding Sites
MH  - Computational Biology/*methods
MH  - Fungal Proteins/metabolism
MH  - *Gene Regulatory Networks
MH  - Genomics
MH  - Plant Proteins/metabolism
MH  - RNA-Binding Proteins/metabolism
MH  - Saccharomyces cerevisiae/genetics/metabolism
MH  - Transcription Factors/metabolism
PMC - PMC3121120
EDAT- 2011/06/28 06:00
MHDA- 2011/10/13 06:00
PMCR- 2011/05/04
CRDT- 2011/06/22 06:00
PHST- 2011/06/22 06:00 [entrez]
PHST- 2011/06/28 06:00 [pubmed]
PHST- 2011/10/13 06:00 [medline]
PHST- 2011/05/04 00:00 [pmc-release]
AID - 1752-0509-5-S1-S4 [pii]
AID - 10.1186/1752-0509-5-S1-S4 [doi]
PST - epublish
SO  - BMC Syst Biol. 2011 May 4;5 Suppl 1(Suppl 1):S4. doi: 10.1186/1752-0509-5-S1-S4.