PMID- 16339286
OWN - NLM
STAT- MEDLINE
DCOM- 20060331
LR  - 20191210
IS  - 1367-4803 (Print)
IS  - 1367-4803 (Linking)
VI  - 22
IP  - 4
DP  - 2006 Feb 15
TI  - Gene sequence signatures revealed by mining the UniGene affiliation network.
PG  - 385-91
AB  - BACKGROUND: In the post-genomic era, developing tools to decode biological 
      information from genomic sequences is important. Inspired by affiliation network 
      theory, we investigated gene sequences of two kinds of UniGene clusters (UCs): 
      narrowly expressed transcripts (NETs), whose expression is confined to a few 
      tissues; and prevalently expressed transcripts (PETs) that are expressed in many 
      tissues. RESULTS: We explored the human and the mouse UniGene databases to 
      compare NETs and PETs from different perspectives. We found that NETs were 
      associated with smaller cluster size, shorter sequence length, a lower likelihood 
      of having LocusLink annotations, and lower and more sporadic levels of 
      expression. Significantly, the dinucleotide frequencies of NETs are similar to 
      those of intergenic sequences in the genome, and they differ from those of PETs. 
      We used these differences in dinucleotide frequencies to develop a discriminant 
      analysis model to distinguish PETs from intergenic sequences. CONCLUSIONS: Our 
      results show that most NETs resemble intergenic sequences, casting doubts on the 
      quality of such UniGene clusters. However, we also noted that a fraction of NETs 
      resemble PETs in terms of dinucleotide frequencies and other features. Such NETs 
      may have fewer quality problems. This work may be helpful in the studies of 
      non-coding RNAs and in the validation of gene sequence databases.
FAU - Zhang, Jiexin
AU  - Zhang J
AD  - Department of Biostatistics and Applied Mathematics, The University of Texas M.D. 
      Anderson Cancer Center, 1515 Holcombe Boulevard, Box 447, Houston, TX 77030-4009, 
      USA.
FAU - Zhang, Li
AU  - Zhang L
FAU - Coombes, Kevin R
AU  - Coombes KR
LA  - eng
PT  - Evaluation Study
PT  - Journal Article
DEP - 20051208
PL  - England
TA  - Bioinformatics
JT  - Bioinformatics (Oxford, England)
JID - 9808944
RN  - 0 (Transcription Factors)
SB  - IM
MH  - Animals
MH  - Chromosome Mapping/*methods
MH  - *Database Management Systems
MH  - *Databases, Genetic
MH  - Humans
MH  - Information Storage and Retrieval/*methods
MH  - Mice
MH  - Multigene Family/*genetics
MH  - Sequence Alignment/*methods
MH  - Sequence Analysis, DNA/*methods
MH  - Transcription Factors/genetics
EDAT- 2005/12/13 09:00
MHDA- 2006/04/01 09:00
CRDT- 2005/12/13 09:00
PHST- 2005/12/13 09:00 [pubmed]
PHST- 2006/04/01 09:00 [medline]
PHST- 2005/12/13 09:00 [entrez]
AID - bti796 [pii]
AID - 10.1093/bioinformatics/bti796 [doi]
PST - ppublish
SO  - Bioinformatics. 2006 Feb 15;22(4):385-91. doi: 10.1093/bioinformatics/bti796. 
      Epub 2005 Dec 8.