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Links tagged with 'stochastic processes'

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AUGUSTUSTool Content

http://bioinf.uni-greifswald.de/augustus

DNA > Gene Prediction
DNA > Structure and Sequence Feature Detection
Expression > Splicing
Protein > Domains and Motifs

AUGUSTUS is a eukaryotic gene prediction tool. It can integrate evidence, e.g. from RNA-Seq, ESTs, proteomics, but can also predict genes ab initio. The PPX extension to AUGUSTUS can take a protein sequence multiple sequence alignment as input to find new members of the family in a genome. It can be run through a web interface, or downloaded and run locally.

This content is being maintained by Mario Stanke.

NAR Web Server Issue 2004NAR Web Server Issue 2005NAR Web Server Issue 2006
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tagsadult algorithms alternative splicing animals artificial intelligence automated pattern recognition base sequence bile acids and salts cholic acids chromosome mapping computer simulation deoxycholic acid dna sequence analysis drosophila melanogaster exons female gene components gene expression genes genetic databases genetic models genetic variation genomics human genome humans hypercholesterolemia hyperlipidemias introns ldl lipoproteins male markov chains middle aged molecular sequence data proteins sequence alignment statistical models stochastic processes triglycerides vldl lipoproteins

CAPwebTool Content

http://bioinfo.curie.fr/CAPweb/

Expression > Transcript Expression Analysis

CGH array Analysis Platform (CAPweb) is a tool for storing, analyzing and visualizing CGH-array data.

NAR Web Server Issue 2006
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tagsalgorithms chromosome breakage chromosome mapping computational biology dna dna mutational analysis dna sequence analysis gene dosage genetic models genetic variation genomics humans in situ hybridization oligonucleotide array sequence analysis reproducibility of results sensitivity and specificity statistical models stochastic processes urinary bladder neoplasms

CytoscapeTool Content

http://www.cytoscape.org/

Protein > Interactions, Pathways, Enzymes

Cytoscape is a visualization platform for use with molecular interaction networks. Interaction data can be integrated with other state data such as gene expression profiles. The input to Cytoscape includes lists of interaction pairs, and tab/space delimited files containing mRNA expression profiles. The nodes of the interaction networks can be filtered by such variables as GO annotations and number of interactions.

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tagsalgorithms archaeal proteins bacteriophage lambda biological models computational biology data mining gene expression profiling gene regulatory networks genomics halobacterium messenger rna neural networks (computer) phenotype protein interaction mapping proteins proteomics software design stochastic processes

DSHIFTTool Content

http://www.chem.cuhk.edu.hk/DSHIFT/

DNA > Structure and Sequence Feature Detection

DSHIFT is a web server for predicting chemical shifts of DNA sequences in random coil form or double helical B-form.

NAR Web Server Issue 2007
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tagsalgorithms base sequence biomolecular nuclear magnetic resonance carbon computational biology computer simulation dna magnetic resonance spectroscopy molecular models molecular sequence data molecular structure nucleic acid conformation oligonucleotides phosphorus programming languages protons reproducibility of results sensitivity and specificity stochastic processes temperature

McPromoterTool Content

http://genes.mit.edu/McPromoter.html

DNA > Structure and Sequence Feature Detection

The Markov Chain Promoter Prediction Server (McPromoter) uses statistics to predict eukaryotic DNA transcription start sites.

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tagsanimals computational biology dna drosophila genetic models genetic promoter regions likelihood functions markov chains neural networks (computer) nucleic acid databases physical chemistry physicochemical phenomena statistical models stochastic processes

MEME SuiteTool Content

http://meme.nbcr.net/meme/intro.html

DNA > Structure and Sequence Feature Detection
Expression > Gene Regulation
Protein > Domains and Motifs
Protein > Sequence Features
Sequence Comparison > Comparative Genomics

The MEME Suite web server is a unified portal for discovery and analysis of sequence motifs (e.g. DNA binding sites, protein interaction domains). Motifs with/without gaps may be discovered, searched for in DNA and protein databases, compared to other motifs and analyzed for putative function by association with gene ontology terms. MEME is a tool designed for discovering and searching for DNA motifs such as transcription factor binding sites (TFBS) or protein domains.

NAR Web Server Issue 2006NAR Web Server Issue 2009
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tagsalcohol dehydrogenase alcohol oxidoreductases algorithms amino acid motifs amino acid sequence amino acid sequence homology animals artificial intelligence automated pattern recognition automation bacterial proteins base sequence binding sites biopolymers chemical models consensus sequence dna dna sequence analysis entropy evaluation studies as topic factual databases ferredoxins genetic databases humans hydroxysteroid dehydrogenases mammals markov chains mathematical computing molecular models molecular sequence data nucleic acid repetitive sequences nucleic acid sequence homology oxidoreductases phylogeny protein sequence analysis proteins reproducibility of results secondary protein structure sequence alignment sequence analysis software design stochastic processes streptomyces tertiary protein structure theoretical models transcription factors transcriptional regulatory elements

Meta-MEMETool Content

http://metameme.sdsc.edu/

DNA > Structure and Sequence Feature Detection
Protein > Domains and Motifs

Creates hidden Markov model of motif from MEME output and searches sequence database for matches to this motif.

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tagsalcohol dehydrogenase algorithms amino acid sequence amino acid sequence homology factual databases ferredoxins markov chains molecular sequence data proteins sequence alignment stochastic processes

PfoldTool Content

http://www.daimi.au.dk/~compbio/pfold

RNA > Structure Prediction, Visualization, and Design

The Pfold server takes an alignment of RNA sequences as input and predicts a common secondary structure.

NAR Web Server Issue 2003
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tagsalgorithms bacterial rna base sequence biological evolution catalytic rna computational biology computer simulation endoribonucleases molecular evolution molecular models molecular sequence data nucleic acid conformation nucleic acid sequence homology probability reproducibility of results ribonuclease p rna rna sequence analysis sequence alignment stochastic processes time factors