RaPPer – Generate Random perfect Phylogeny Matrix

RaPPer

:: DESCRIPTION

RaPPer will generate random perfect phylogeny matrix with following conditions.

::DEVELOPER

School of Biological Sciences, Iran

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOsX
  • MatLab

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Adv Appl Bioinform Chem. 2010;3:89-96. doi: 10.2147/AABC.S13397. Epub 2010 Nov 16.
Construction of random perfect phylogeny matrix.
Sadeghi M1, Pezeshk H, Eslahchi C, Ahmadian S, Abadi SM.

RaPID 1.7 – Random Projection-based IBD Detection

RaPID 1.7

:: DESCRIPTION

RaPID is a software of ultra-fast identity by descent (IBD) detection in large cohorts using positional Burrows-Wheeler transform

::DEVELOPER

UCF Computational Biology and Bioinformatics Group

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux
  • Java

:: DOWNLOAD

RaPID

:: MORE INFORMATION

Citation

RaPID: ultra-fast, powerful, and accurate detection of segments identical by descent (IBD) in biobank-scale cohorts.
Naseri A, Liu X, Tang K, Zhang S, Zhi D.
Genome Biol. 2019 Jul 25;20(1):143. doi: 10.1186/s13059-019-1754-8.

ABCRF 1.8 – Approximate Bayesian Computation via Random Forests

ABCRF 1.8

:: DESCRIPTION

ABCRF is an R library to perform Approximate Bayesian Computation (ABC) model choice and parameter inference via random forests.

::DEVELOPER

The Computational Biology Institute (IBC)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux /macOsX
  • R

:: DOWNLOAD

ABCRF

:: MORE INFORMATION

Citation

Bioinformatics. 2019 May 15;35(10):1720-1728. doi: 10.1093/bioinformatics/bty867.
ABC random forests for Bayesian parameter inference.
Raynal L, Marin JM, Pudlo P, Ribatet M, Robert CP, Estoup A

RDDpred 1.0 – Random Forest RDD Classifier

RDDpred 1.0

:: DESCRIPTION

RDDpred is a condition-specific RNA-editing prediction model from RNA-seq data.

::DEVELOPER

Bio & Health Informatics Lab, SNU

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 RDDpred

:: MORE INFORMATION

Citation

RDDpred: a condition-specific RNA-editing prediction model from RNA-seq data.
Kim MS, Hur B, Kim S.
BMC Genomics. 2016 Jan 11;17 Suppl 1:5. doi: 10.1186/s12864-015-2301-y.

pSuc-Lys – Predict Lysine Succinylation sites in Proteins with PseAAC and Ensemble Random Forest Approach

pSuc-Lys

:: DESCRIPTION

The web-server pSuc-Lys used to predict the lysine succinylation in protein.

::DEVELOPER

JCI BioInfo Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach.
Jia J, Liu Z, Xiao X, Liu B, Chou KC.
J Theor Biol. 2016 Jan 22. pii: S0022-5193(16)00053-9. doi: 10.1016/j.jtbi.2016.01.020

RANDNA – Random DNA Sequence Generator

RANDNA

:: DESCRIPTION

RANDNA is a free software which allows to create random DNA sequences setting both their length and the percentage of nucleotide composition.

::DEVELOPER

Gruppo di Biologia Computazionale

:: SCREENSHOTS

RANDNA

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 RANDNA

:: MORE INFORMATION

Citation:

In Silico Biol. 2006;6(3):253-8.
RANDNA: a random DNA sequence generator.
Piva F1, Principato G.

PaRFR – Parallel Random Forest Regression for Hadoop

PaRFR

:: DESCRIPTION

PaRFR is a parallel version of RF for regression tasks with both univariate and multivariate responses  to support multivariate quantitative trait loci mapping in unrelated subjects.

::DEVELOPER

Giovanni Montana @ Imperial College London

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R package

:: DOWNLOAD

 PaRFR

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2013;14 Suppl 16:S6. doi: 10.1186/1471-2105-14-S16-S6. Epub 2013 Oct 22.
Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.
Wang Y, Goh W, Wong L, Montana G; Alzheimer’s Disease Neuroimaging Initiative.

GenRGenS 2.1 – Generation of Random Genomic Sequences and Structures

GenRGenS 2.1

:: DESCRIPTION

GenRGenS is a software dedicated to random generation of genomics sequences that supports several classes of models, including Markov chains, HMM, context-free grammars, PROSITE patterns and more.

::DEVELOPER

GenRGenS Team 

:: SCREENSHOTS

GenRGenS

:: REQUIREMENTS

  • Windows / MacOsX / Linux
  • Java

:: DOWNLOAD

 GenRGenS

:: MORE INFORMATION

Citation

Y. Ponty, M. Termier and A. Denise [pdf] [bib]
GenRGenS: Software for generating random genomic sequences and structures
Bioinformatics, June 2006 22(12):1534-1535.