Sciweavers

Share
warning: Creating default object from empty value in /var/www/modules/taxonomy/taxonomy.module on line 1416.
NAR
2011
209views Computer Vision» more  NAR 2011»
11 years 4 months ago
CancerResource: a comprehensive database of cancer-relevant proteins and compound interactions supported by experimental knowled
During the development of methods for cancer diagnosis and treatment, a vast amount of information is generated. Novel cancer target proteins have been identified and many compoun...
Jessica Ahmed, Thomas Meinel, Mathias Dunkel, Manu...
NAR
2011
214views Computer Vision» more  NAR 2011»
11 years 4 months ago
starBase: a database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data
MicroRNAs (miRNAs) represent an important class of small non-coding RNAs (sRNAs) that regulate gene expression by targeting messenger RNAs. However, assigning miRNAs to their regu...
Jian-Hua Yang, Jun-Hao Li, Peng Shao, Hui Zhou, Yu...
BMCBI
2011
11 years 5 months ago
Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities
Background: Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Un...
Yao Fu, Laura R. Jarboe, Julie A. Dickerson
NAR
2008
174views more  NAR 2008»
12 years 12 days ago
miRGator: an integrated system for functional annotation of microRNAs
MicroRNAs (miRNAs) constitute an important class of regulators that are involved in various cellular and disease processes. However, the functional significance of each miRNA is m...
Seungyoon Nam, Bumjin Kim, Seokmin Shin, Sanghyuk ...
NAR
2007
132views more  NAR 2007»
12 years 1 months ago
TRED: a transcriptional regulatory element database, new entries and other development
Transcriptional factors (TFs) and many of their target genes are involved in gene regulation at the level of transcription. To decipher gene regulatory networks (GRNs) we require ...
C. Jiang, Zhenyu Xuan, Fang Zhao, Michael Q. Zhang
BMCBI
2007
169views more  BMCBI 2007»
12 years 1 months ago
Transcription factor target prediction using multiple short expression time series from Arabidopsis thaliana
Background: The central role of transcription factors (TFs) in higher eukaryotes has led to much interest in deciphering transcriptional regulatory interactions. Even in the best ...
Henning Redestig, Daniel Weicht, Joachim Selbig, M...
BMCBI
2007
148views more  BMCBI 2007»
12 years 1 months ago
p53FamTaG: a database resource of human p53, p63 and p73 direct target genes combining in silico prediction and microarray data
Background: The p53 gene family consists of the three genes p53, p63 and p73, which have polyhedral non-overlapping functions in pivotal cellular processes such as DNA synthesis a...
Elisabetta Sbisà, Domenico Catalano, Giorgi...
BIOINFORMATICS
2006
118views more  BIOINFORMATICS 2006»
12 years 2 months ago
A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription
Motivation Quantitative estimation of the regulatory relationship between transcription factors and genes is a fundamental stepping stone when trying to develop models of cellular...
Guido Sanguinetti, Magnus Rattray, Neil D. Lawrenc...
BMCBI
2008
110views more  BMCBI 2008»
12 years 2 months ago
Finding microRNA regulatory modules in human genome using rule induction
Background: MicroRNAs (miRNAs) are a class of small non-coding RNA molecules (20
Dang Hung Tran, Kenji Satou, Tu Bao Ho
BMCBI
2010
160views more  BMCBI 2010»
12 years 2 months ago
Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53
Background: The availability of various "omics" datasets creates a prospect of performing the study of genomewide genetic regulatory networks. However, one of the major ...
Junbai Wang, Tianhai Tian
books