TSNI / TSNI-integral – Time Series Network Identification

TSNI / TSNI-integral

:: DESCRIPTION

TSNI assumes that the gene network can be modeled by the following system of ordinary differential equation to represent the rate of synthesis of a transcript as a function of the concentrations of every other transcript in a cell and the external perturbation.

TSNI-integral

::DEVELOPER

di Bernardo Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • MatLab

:: DOWNLOAD

  TSNI / TSNI-integral 

:: MORE INFORMATION

Citation

IET Syst Biol. 2007 Sep;1(5):306-12.
Inference of gene networks from temporal gene expression profiles.
Bansal M, di Bernardo D.

StarORF – Identification of the Protein(s) Encoded within a DNA sequence

StarORF

:: DESCRIPTION

StarORF facilitates the identification of the protein(s) encoded within a DNA sequence. Using StarORF, the DNA sequence is first transcribed into RNA and then translated into all the potential ORFs (Open Reading Frame) encoded within each of the six translation frames (3 in the forward direction and 3 in the reverse direction).

:: DEVELOPER

The STAR program at MIT

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

 StarORF

:: MORE INFORMATION

ThioFinder 1.2 – Identification of Thiopeptide Gene Clusters in DNA sequences

ThioFinder 1.2

:: DESCRIPTION

ThioFinder is a web-based tool  to rapidly identify thiopeptide biosynthetic gene cluster from DNA sequence using a profile Hidden Markov Model approach.

::DEVELOPER

Microbial Genomics and Bioinformatics Group, SKMML, SJT

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

PLoS One. 2012;7(9):e45878. doi: 10.1371/journal.pone.0045878.
ThioFinder: a web-based tool for the identification of thiopeptide gene clusters in DNA sequences.
Li J, Qu X, He X, Duan L, Wu G, Bi D, Deng Z, Liu W, Ou HY.

TSRchitect 1.20.0 – Promoter Identification from large-scale TSS Profiling data

TSRchitect 1.20.0

:: DESCRIPTION

TSRchitect allows the user to efficiently identify the putative promoter (the transcription start region, or TSR) from a variety of TSS profiling data types, including both single-end (e.g. CAGE) as well as paired-end (RAMPAGE, PEAT, STRIPE-seq).

::DEVELOPER

The Brendel Group @ Indiana University

:: REQUIREMENTS

  • Linux
  • R
  • Bioconductor

:: DOWNLOAD

TSRchitect

:: MORE INFORMATION

Citation

Raborn RT, Brendel VP.
Using RAMPAGE to Identify and Annotate Promoters in Insect Genomes.
Methods Mol Biol. 2019;1858:99-116. doi: 10.1007/978-1-4939-8775-7_9. PMID: 30414114.

MetWAMer 1.3.3 – Translation Initiation Site (TIS) Identification

MetWAMer 1.3.3

:: DESCRIPTION

MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the k-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5′-complete coverage.

::DEVELOPER

The Brendel Group @ Indiana University

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

MetWAMer

:: MORE INFORMATION

Citation

Sparks, M.E. & Brendel, V. (2008)
MetWAMer: eukaryotic translation initiation site prediction.
BMC Bioinformatics, 9, 381.

H2r – Identification of Evolutionary Important Residues

H2r

:: DESCRIPTION

H2r is a online web server of identification of important residue-sites by means of an entropy based analysis of multiple sequence alignments

::DEVELOPER

Computational Protein Design and Evolution at the University of Regensburg

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

MC Bioinformatics. 2008 Mar 18;9:151. doi: 10.1186/1471-2105-9-151.
H2r: identification of evolutionary important residues by means of an entropy based analysis of multiple sequence alignments.
Merkl R, Zwick M.

Marina 1.03 – Identification of Over/under-represented TFBSs given large sets of Promoter-sequences

Marina 1.03

:: DESCRIPTION

Marina is an OS-independent GUI tool for computing TFBS abundance given two sets of promoter sequences. Marina performs such computations by harnessing 7 knowledge-discovery statistical metrics and the hypergeometric distribution so as to infer magnitude of TFBS over-representation. A standardization algorithm known as Iterative Proportional Fitting (IPF) enables “agreement” across these various metrics as to which TFBSs are the most over-represented and which are not.

::DEVELOPER

Parsa Hosseini

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Java

:: DOWNLOAD

 Marina

:: MORE INFORMATION

Citation

Plant Methods. 2013 Apr 11;9(1):12. doi: 10.1186/1746-4811-9-12.
Using an ensemble of statistical metrics to quantify large sets of plant transcription factor binding sites.
Hosseini P, Ovcharenko I, Matthews BF.

LcaMap – Simultaneous Identification of Duplications, Losses and Lateral Gene Transfers

LcaMap

:: DESCRIPTION

LcaMap is a software for simultaneous identification of duplication, losses and lateral gene transfers. LcaMap takes a gene tree G, a species tree S, and the costs of a lateral gene transfer, a gene duplication, and a gene loss as its input. It outputs all minimum-cost LCA-reconciliations between G and S.

::DEVELOPER

Lusheng Wang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux

:: DOWNLOAD

 LcaMap

:: MORE INFORMATION

SEGID – Conserved Segment Identification

SEGID

:: DESCRIPTION

SEGID is a bioinformatics webtool for conserved SEGment IDentification. The software is a sequence analysis tool designed to identify conserved segments in a (multiple) sequence alignment. Conserved segments are high-scoring substrings in a long alignment which are probably biologically meaningful. SEGID accepts an alignment, converts the alignment into a sequence of numbers, one for each column, identifies its conserved segments, and generates graphical output. (It can also directly accept a sequence of numbers as input.)

::DEVELOPER

Lusheng Wang ,  Ying Xu

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows /Linux/MacOsX
  • Java

:: DOWNLOAD

 SEGID

:: MORE INFORMATION

Citation

Lusheng Wang, Ying Xu,
SEGID: identifying interesting segments in sequence alignments,
Bioinformatics, 19(2), 2003;

GWAS Pathway Identifier 1.0.0 – Pathway- and Protein-Interaction-Based Identification of Disease Specific SNP Sets in GWAS

GWAS Pathway Identifier 1.0.0

:: DESCRIPTION

GWAS Pathway Identifier combines GWAS(Genome-Wide Accociation Studies) and pathway data as well as known and predicted protein-interaction data to identify disease specific SNP sets.

::DEVELOPER

the Interfaculty Institute for Biomedical Informatics (IBMI)

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

 GWAS Pathway Identifier

:: MORE INFORMATION

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