newDNA-Prot – DNA Binding Protein Predict Software

newDNA-Prot

:: DESCRIPTION

newDNA-Prot will predict the DNA-binding proteins when input a protein sequence (Fasta format).

::DEVELOPER

newDNA-Prot team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows
  • fortran-windows

:: DOWNLOAD

newDNA-Prot

:: MORE INFORMATION

Citation

newDNA-Prot: Prediction of DNA-binding proteins by employing support vector machine and a comprehensive sequence representation.
Zhang Y, Xu J, Zheng W, Zhang C, Qiu X, Chen K, Ruan J.
Comput Biol Chem. 2014 Oct;52:51-9. doi: 10.1016/j.compbiolchem.2014.09.002.

PromFD 1.0 – Predict Promoter Regions in DNA Sequences

PromFD 1.0

:: DESCRIPTION

PromFD is a computer program to recognize vertebrate RNA polymerase II promoters

::DEVELOPER

Stormo Lab in Department of Genetics, Washington University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler

:: DOWNLOAD

 PromFD

:: MORE INFORMATION

Citation

Comput Appl Biosci. 1997 Feb;13(1):29-35.
PromFD 1.0: a computer program that predicts eukaryotic pol II promoters using strings and IMD matrices.
Chen QK, Hertz GZ, Stormo GD.

MiRScan 3 – Predict microRNA Genes from pairs of Conserved Sequences

MiRScan 3

:: DESCRIPTION

MiRScan is a computational procedure to identify miRNA genes conserved in more than one genome.

MiRScan Online Version

::DEVELOPER

Christopher Burge Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/MacOsX/Linux
  • Python

:: DOWNLOAD

 MiRScan

:: MORE INFORMATION

Citation

Genome Res. 2007 Dec;17(12):1850-64. Epub 2007 Nov 7.
Evolution, biogenesis, expression, and target predictions of a substantially expanded set of Drosophila microRNAs.
Ruby JG, Stark A, Johnston WK, Kellis M, Bartel DP, Lai EC.

The microRNAs of Caenorhabditis elegans.
Lim LP, Lau NC, Weinstein EG, Abdelhakim A, Yekta S, Rhoades MW, Burge CB, Bartel DP.
Genes Dev. 2003 Apr 15;17(8):991-1008. Epub 2003 Apr 2.

ILM 1.0 – Predict RNA Secondary Structures with Pseudoknots

ILM 1.0

:: DESCRIPTION

 ILM (Iterated Loop Matching) is a web server for predicting RNA secondary structures with pseudoknots.

::DEVELOPER

Jianhua Ruan

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/MacOsX
  • C Compiler

:: DOWNLOAD

 ILM

:: MORE INFORMATION

Citation

Ruan J, Stormo GD and Zhang W.
An Iterated loop matching approach to the prediction of RNA secondary structures with pseudoknots“,
Bioinformatics. 2004 Jan 1;20(1):58-66.

DriverNet 1.0.0 – Predict Functional Important Driver Genes in Cancer Genome

DriverNet 1.0.0

:: DESCRIPTION

DriverNet is a package to predict functional important driver genes in cancer by integrating genome data (mutation and copy number variation data) and transcriptome data (gene expression data). The different kinds of data are combined by an influence graph, which is a gene-gene interaction network deduced from pathway data. A greedy algorithm is used to find the possible driver genes, which may mutated in a larger number of patients and these mutations will push the gene expression values of the connected genes to some extreme values.

::DEVELOPER

Shah Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • R package

:: DOWNLOAD

  DriverNet

:: MORE INFORMATION

Citation

Genome Biol. 2012 Dec 22;13(12):R124.
DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer.
Bashashati A, Haffari G, Ding J, Ha G, Lui K, Rosner J, Huntsman DG, Caldas C, Aparicio SA, Shah SP.

FlexS 2.1.3 – Predict Ligand Superpositions

FlexS 2.1.3

:: DESCRIPTION

FlexS is a computer program for predicting ligand superpositions. For a given pair of ligands, FlexS predicts the conformation and orientation of one of the ligands relative to the other one. In FlexS the reference-ligand is assumed to be rigid, thus, it should be given in a conformation which is similar to the bound state. The superposition algorithm in FlexS requires only little manual intervention. Nevertheless, in some cases additional information about the ligands or even the superposition is known. You can integrate this knowledge into the computations with FlexS by carrying out single steps manually. Thus, FlexS is designed for interactive work on ligand pairs as well as for ligand-based virtual screening.

::DEVELOPER

BioSolveIT GmbH 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/SGI Irix

:: DOWNLOAD

 FlexS

:: MORE INFORMATION

Citation

C. Lemmen, T. Lengauer, and G. Klebe.
FLEXS: A method for fast flexible ligand superposition.
Journal of Medicinal Chemistry, 41:4502–4520, 1998.

CpGProD – Predict Mammalian Promoters Associated with CpG Islands

CpGProD

:: DESCRIPTION

CpGProD (CpG Island Promoter Detection) is an application for identifying mammalian promoter regions associated with CpG islands in large genomic sequences. Although it is strictly dedicated to this particular promoter class corresponding to ≈50% of the genes, CpGProD exhibits a higher sensitivity and specificity than other tools used for promoter prediction. Notably, CpGProD uses different parameters according to species (human, mouse) studied. Moreover, CpGProD predicts the promoter orientation on the DNA strand.

CpGProD Online Version

::DEVELOPER

PRABI-Doua

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows /  Mac OsX / Linux

:: DOWNLOAD

 CpGProD

:: MORE INFORMATION

Citation

Ponger, L. and Mouchiroud, D. (2001)
CpGProD: identifying CpG islands associated with transcription start sites in large genomic mammalian sequences.
Bioinformatics, 18, 631-633

NeuroPIpred – Tool to Predict, Design and Scan Insect Neuropeptides

NeuroPIpred

:: DESCRIPTION

NeuroPIpred is an in silico method, which is developed to predict and design insect neuropeptides with better efficacy for controlling pest from infesting various crops.

::DEVELOPER

NeuroPIpred team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

NeuroPIpred: a tool to predict, design and scan insect neuropeptides.
Agrawal P, Kumar S, Singh A, Raghava GPS, Singh IK.
Sci Rep. 2019 Mar 26;9(1):5129. doi: 10.1038/s41598-019-41538-x.

CHpredict – Predict C-H…O and C-H…PI Interactions

CHpredict

:: DESCRIPTION

The CHpredict server predict two types of interactions: C-H…O and C-H…PI interactions. For C-H…O interaction, the server predicts the residues whose backbone Calpha atoms are involved in interaction with backbone oxygen atoms and for C-H…PI interactions, it predicts the residues whose backbone Calpha atoms are involved in interaction with PI ring system of side chain aromatic moieties.

::DEVELOPER

CHpredict Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Kaur, H. and Raghava, G.P.S. (2006)
Prediction of Cα-H…O and Cα-H…π interactions in proteins using recurrent neural network. 
In-Silico Biology 6, 0011

BetaTPred – Predict Beta Turns in Proteins using Existing Statistical methods

BetaTPred

:: DESCRIPTION

The server BetaTPredis developed for predicting Beta-turns in a protein from the amino acid sequence.

::DEVELOPER

BetaTPred Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Kaur, H. and Raghava, G.P.S. (2002)
BetaTpred:Prediction of beta-turns in a protein using statistical algorithms.
Bioinformatics 18:498-9