Tag: Position

CLIPS-1D / CLIPS-4D – Predicting Functionally and Structurally Important Residue-positions based on 1D / and 3D data

CLIPS-1D / CLIPS-4D

:: DESCRIPTION

CLIPS-1D / CLIPS-4D: Predicting functionally and structurally importand residues by means of a multiclass support vector machine

::DEVELOPER

Computational Protein Design and Evolution at the University of Regensburg

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2012 Apr 5;13:55. doi: 10.1186/1471-2105-13-55.
CLIPS-1D: analysis of multiple sequence alignments to deduce for residue-positions a role in catalysis, ligand-binding, or protein structure.
Janda JO, Busch M, Kück F, Porfenenko M, Merkl R.

Bioinformatics. 2013 Oct 4.
CLIPS-4D: a classifier that distinguishes structurally and functionally important residue-positions based on sequence and 3D data.
Janda JO, Meier A, Merkl R.

Morpheus 2.0 – Prediction of Transcription Factors Binding Sites based on Position Weight Matrix

Morpheus 2.0

:: DESCRIPTION

Morpheus offers a range of tools to analyze transcription factor binding sites (TFBS) on DNA sequences.

::DEVELOPER

BIODEV

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Python

:: DOWNLOAD

 Morpheus

:: MORE INFORMATION

TFM-Scan – Efficient Location of Position Weight Matrices on a DNA sequence

TFM-Scan

:: DESCRIPTION

TFM-Scan is a program dedicated to the location of large sets of putative transcription factor binding sites on a DNA sequence.

::DEVELOPER

Bonsai Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/Windows
  • C++ Compiler

 TFM-Scan

:: MORE INFORMATION

Citation

Large scale matching for Position Weight Matrices
Liefooghe A., Touzet H. and Varré J.-S.
In Combinatorial Pattern Matching, volume 4009 of Lecture Notes in Computer Science, pages 401-412. Springer Verlag, 2006.

iNuc-force – Identify Nucleosome Positions in Genome

iNuc-force

:: DESCRIPTION

iNuc-force allows for discriminating nucleosome-enriched regions from nucleosome-depleted regions.

::DEVELOPER

LinDing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

DNA physical properties outperform sequence compositional information in classifying nucleosome-enriched and -depleted regions.
Liu G, Liu GJ, Tan JX, Lin H.
Genomics. 2019 Sep;111(5):1167-1175. doi: 10.1016/j.ygeno.2018.07.013.

NucleoFinder 1.0 – Detection of Nucleosome Positions

NucleoFinder 1.0

:: DESCRIPTION

NucleoFinder addresses both the positional heterogeneity across cells and experimental biases by seeking nucleosomes consistently positioned in a cell population and showing a significant enrichment relative to a control sample.

:: DEVELOPER

Chris Holmes

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • R package

:: DOWNLOAD

 NucleoFinder

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Mar 15;29(6):711-716. Epub 2013 Jan 6.
NucleoFinder: a statistical approach for the detection of nucleosome positions.
Becker J, Yau C, Hancock JM, Holmes CC.