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Ongoing advances in sequencing technology and computational methods have enabled the collection and analysis of vast amounts of molecular data from diverse biological communities.
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The EcoliNet server (http://www.inetbio.org/ecolinet) provides not only public prediction tools but also a database of cofunctional associations between E. coli genes, derived from diverse biological data.
Tangible examples include system-wide glycoproteomics studies detecting thousands of intact glycopeptides from hundreds of glycoproteins from diverse biological samples.
The remaining genes with low LNS are from diverse biological processes and functions.
We implemented an annotation algorithm that integrates knowledge from diverse biological databases to characterize each RNA-seq read.
EMPReSSslim captures a broad range of data on diverse biological systems, from biochemical to physiological amongst others.
BioMart uses a federated data model to allow integration of biological data from diverse databases (1).
Emerging data collection technologies provide a multitude of rich data from diverse data sources.
Modern classifications serve as informatics devices capable of linking, integrating and retrieving information contained in diverse biological data sets.
The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms.
A wealthy amount of diverse biological data from barley germination has been accumulated [ 24].
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