Tag: Rank

ProtDec-LTR 3.0 – Application of Learning to Rank to Protein Remote Homology detection

ProtDec-LTR 3.0

:: DESCRIPTION

ProtDec-LTR is an method for protein remote homology detection by combining pseudo protein and supervised learning to rank

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Liu B, et al.
ProtDec-LTR3.0: protein remote homology detection by embedding sequence-based features into learning to rank,
IEEE ACCESS 2019; 7:102499-102507.

Chen J, Guo M, Li S, Liu B.
ProtDec-LTR2.0: an improved method for protein remote homology detection by combining pseudo protein and supervised Learning to Rank.
Bioinformatics. 2017 Nov 1;33(21):3473-3476. doi: 10.1093/bioinformatics/btx429. PMID: 29077805.

Liu B, Chen J, Wang X.
Application of learning to rank to protein remote homology detection.
Bioinformatics. 2015 Nov 1;31(21):3492-8. doi: 10.1093/bioinformatics/btv413. Epub 2015 Jul 10. PMID: 26163693.

GATOR 1.0 – Genetic Association Tests Based on Ranks

GATOR 1.0

:: DESCRIPTION

GATOR (Genetic Association Tests Based on Ranks) is a program that implements the family-based association method for quantitative traits with and without censoring described in Allen et al. (2006). This program is distinctive in that it can handle quantitative phenotypes with skewed distributions, censored data, and/or outliers. Currently the program focuses on bi-allelic markers (e.g. single nucleotide polymorphisms). It can handle parent-offspring (Triads), sibships with (Quads) and without (Sibs) parents, and extended multi-generation pedigree data (General Pedigree). GATOR is able to perform association tests using four different genetic models: general, dominant, recessive, and additive.

::DEVELOPER

Duke Molecular Physiology Institute

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux

:: DOWNLOAD

 GATOR

:: MORE INFORMATION

Citation

Allen AS., Martin E., Qin X., Li Y.J:
Genetic Association Tests Based on Ranks (GATOR) for Quantitative Traits With and Without Censoring.
Genetic Epidemiology 2006; 30: 248-258.

DockRank – Rank Docked Models Using Predicted Partner-Specific Protein-Protein Binding Sites

DockRank

:: DESCRIPTION

DockRank is a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues.

::DEVELOPER

Artificial Intelligence Research Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Proteins. 2014 Feb;82(2):250-67. doi: 10.1002/prot.24370. Epub 2013 Oct 17.
DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.
Xue LC1, Jordan RA, El-Manzalawy Y, Dobbs D, Honavar V.

staRank 1.28.0 – Ranking Variables based on their Stability

staRank 1.28.0

:: DESCRIPTION

staRank is an R package for ranking variables based on their stability.Detecting all relevant variables from a data set is challenging, especially when only few samples are available and data is noisy. Stability ranking provides improved variable rankings of increased robustness using resampling or subsampling.

::DEVELOPER

the Computational Biology Group (CBG)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  staRank

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Apr 17. [Epub ahead of print]
Stability of gene rankings from RNAi screens.
Siebourg J, Merdes G, Misselwitz B, Hardt WD, Beerenwinkel N.

PeakSeq 1.31 – Identify and Rank Peak Regions in ChIP-Seq Experiments

PeakSeq 1.31

:: DESCRIPTION

PeakSeq is a program for identifying and ranking peak regions in ChIP-Seq experiments. It takes as input, mapped reads from a ChIP-Seq experiment, mapped reads from a control experiment and outputs a file with peak regions ranked with increasing Q-values.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 PeakSeq

:: MORE INFORMATION

Citation:

Rozowsky J, Euskirchen G, Auerbach R, Zhang Z, Gibson T, Bjornson R, Carriero N, Snyder M, Gerstein M
PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls
Nature Biotechnology 27, 66 – 75 (2009).

GFold 1.1.4 – Generalized fold change for Rank Differentially Expressed Genes from RNA-seq data

GFold 1.1.4

:: DESCRIPTION

gfold (Generalized fold change) generalizes the fold change by considering the posterior distribution of log fold change, such that each gene is assigned a reliable fold change. It overcomes the shortcoming of p-value that measures the significance of whether a gene is differentially expressed under different conditions instead of measuring relative expression changes, which are more interesting in many studies. It also overcomes the shortcoming of fold change that suffers from the fact that the fold change of genes with low read count are not so reliable as that of genes with high read count, even these two genes show the same fold change.

::DEVELOPER

X. Shirley Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 GFold

:: MORE INFORMATION

Citation

Feng J, Meyer CA, Wang Q, Liu JS, Liu XS, Zhang Y.
GFOLD: a generalized fold change for ranking differentially ex-pressed genes from RNA-seq data.
Bioinformatics (2012) 28 (21): 2782-2788.

TargetRank 1.0 – Rank Conserved and non-conserved microRNA Targets and siRNA off-targets

TargetRank 1.0

:: DESCRIPTION

 TargetRank is a webtool for ranking conserved and non-conserved microRNA targets and siRNA off-targets.

::DEVELOPER

Christopher Burge Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nielsen, C.B., Shomron, N., Sandberg, R., Hornstein, E., Kitzman, J. and Burge, C.G. (2007).
Determinants of targeting by endogeno us and exogenous microRNAs and siRNAs.
RNA 13, 1894-1910.

Rankgene 1.1 – Rank Genes from Expression data

Rankgene 1.1

:: DESCRIPTION

 Rankgene is a program for analyzing gene expression data, feature selection and ranking genes based on the predictive power of each gene to classify samples into functional or disease categories.

::DEVELOPER

Computational Genomics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Rankgene

:: MORE INFORMATION

Citation:

RankGene: identification of diagnostic genes based on expression data.
Su Y, Murali TM, Pavlovic V, Schaffer M, Kasif S.
Bioinformatics. 2003 Aug 12;19(12):1578-9.

Quasar 1.2 – Score & Rank Sequence-structure Alignments

Quasar 1.2

:: DESCRIPTION

Quasar (quality of sequence–structure alignments ranking)  is a flexible tool for calculating quality scores of sequence-structure alignments. The main reason for its flexibility is that you do not have to write any additional Java code in order to combine single alignment quality scores (also called scoring schemes) to scoring function (done by score conductors) but you only have to provide the system a XML – like configuration file.

::DEVELOPER

Institut für Informatik, Ludwig-Maximilians-Universität München

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

Quasar

:: MORE INFORMATION

Citation

Fabian Birzele, Jan Gewehr, Ralf Zimmer.
QUASAR–scoring and ranking of sequence-structure alignments.
Bioinformatics, vol 21, no. 24, pp. 4425–4426, Dec 2005.