Pathway – Heritable Clustering Algorithms

Pathway

:: DESCRIPTION

Pathway uses methylation profiles and clinical variables to group tumor samples into clusters and then organize them into a tree to represent tumor progression pathways that conform to strict heritability.

::DEVELOPER

Statistical Genetics and Bioinformatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • MATLAB

:: DOWNLOAD

  Pathway

:: MORE INFORMATION

Citation

Wang, Z., Yan, P., Potter, D., Eng, C., Huang, T.H., Lin, S. (2005)
Heritable Clustering Algorithms – Recapitulation of Breast Tumor Progression Pathways Using DNA Methylation Data.

SARA 1.0 – Side-chain Angular Replacement Algorithm

SARA 1.0

:: DESCRIPTION

SARA is a very fast method for doing single side chain replacements in protein structures by using a coarse- grained method. It is over five times faster than the leading all-atom approach, and generates biologically realistic side-chain angles. The solutions found by SARA typically deviate less than 1 ? and 12 degrees from native structures or the best all-atom solution. Run-time for the algorithm is highly predictable and can easily be tuned by the user. These characteristics makes SARA an excellent choice for high-throughput applications like structural genomics, evolutionary simulations and structure-based phylogenetics.

::DEVELOPER

Liberles Research Group.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 SARA

:: MORE INFORMATION

Citation

J Mol Evol. 2011 Aug;73(1-2):23-33. Epub 2011 Jul 29.
Fast side chain replacement in proteins using a coarse-grained approach for evaluating the effects of mutation during evolution.
Grahnen JA, Kubelka J, Liberles DA.

CompareProspector – Sequence Motif Finding Algorithm

CompareProspector

:: DESCRIPTION

CompareProspector is a sequence motif-finding algorithm which extends Gibbs sampling by biasing the search in promoter regions conserved across species. Using human–mouse comparison, CompareProspector correctly identified the known motifs for transcription factors Mef2, Myf, Srf, and Sp1 from a set of human muscle-specific genes. It also discovered the NFAT motif from genes upregulated by CD28 stimulation in T cells, which suggests the direct involvement of NFAT in mediating CD28 stimulatory signal. Using C. elegans–C. briggsae comparison, CompareProspector found the PHA-4 motif from pharyngeally expressed genes and the UNC-86 motif from genes known to be regulated by UNC-86. CompareProspector outperformed many other computational motif-finding programs tested, demonstrating the power of comparative genomics-based biased sampling in eukaryotic regulatory element identification.

::DEVELOPER

X. Shirley Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows with Cygwin / Linux / Mac OsX
  • C Complier

:: DOWNLOAD

 CompareProspector

:: MORE INFORMATION

Citation:

Liu Y, Liu XS, Wei L, Altman RB, Batzoglou S.
Eukaryotic regulatory element conservation analysis and identification using comparative genomics.
Genome Res. 2004 Mar;14(3):451-8.

scikit-bio 0.5.5 – Python 3 package providing Data Structures, Algorithms and Educational Resources for Bioinformatics

scikit-bio 0.5.5

:: DESCRIPTION

scikit-bio is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics.

::DEVELOPER

Knight Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows /MacOsX
  • Python

:: DOWNLOAD

scikit-bio

:: MORE INFORMATION

GeneStitch 1.2.1 – Network Matching Algorithm to Gene Assembly

GeneStitch 1.2.1

:: DESCRIPTION

GeneStitch is a tool to assemble genes using network matching algorithm. Given an already-assembled dataset, it is capable of assembling contigs together to form more complete genes with the help of a reference gene set. Currently the assembly software that GeneStitch support is SOAPdenovo.

::DEVELOPER

Yuzhen Ye lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

  GeneStitch

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Sep 15;28(18):i363-i369. doi: 10.1093/bioinformatics/bts388.
Stitching gene fragments with a network matching algorithm improves gene assembly for metagenomics.
Wu YW, Rho M, Doak TG, Ye Y.

BOQA – Bayesian Ontology Query Algorithm

BOQA

:: DESCRIPTION

BOQA integrates the knowledge stored in an ontology and the accompanying annotations into a Bayesian network in order to implement a search system in which users enter one or more terms of the ontology to get a list of appropriate domain items.

::DEVELOPER

Phenomics Berlin Home

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

BOQA

:: MORE INFORMATION

Citation

Sebastian Bauer, Sebastian Köhler, Marcel H. Schulz and Peter N. Robinson
Bayesian Ontology Querying for Accurate and Noise-Tolerant Semantic Searches
Bioinformatics (2012) doi: 10.1093/bioinformatics/b

LaJolla 2.2.1 – Peer Reviewed Algorithm for the 3D Alignment

LaJolla 2.2.1

:: DESCRIPTION

LaJolla is a peer reviewed algorithm for the 3D alignment of RNA and protein structures. It uses n-gram based indexing and produces a set of 3D superpositions to found substructures.LaJolla can perform 3D alignments of RNA and protein structures. It is fast, simple to use and well tested.

::DEVELOPER

LaJolla Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Java

:: DOWNLOAD

LaJolla

:: MORE INFORMATION

Citation

Bauer, R.; Rother, K.; Moor, P.; Reinert, K.; Steinke, T.; Bujnicki, J. M.; Preissner, R.
Fast Structural Alignment of Biomolecules Using a Hash Table, N-Grams and String Descriptors.
Algorithms 2009, 2, 692-709.

NRProF – Protein Function Prediction Based on the Neural Response Algorithm

NRProF

:: DESCRIPTION

 NRProF is a novel automated protein functional assignment method based on the neural response algorithm, which simulates the neuronal behavior of the visual cortex in the human brain. The main idea of this algorithm is to define a distance metric that corresponds to the similarity of the subsequences and reflects how the human brain can distinguish between different sequences. We predicted the most similar target protein for a given query protein using the two layered neural response algorithm and thereby assigned the GO term associated with the target sequence to the query sequence. Our method predicted and ranked the actual GO term in the first position out of five with an accuracy of 82%. Results of the 5-fold cross validation and the comparison with PFP server indicate the better performance by our method.

::DEVELOPER

JJWang Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOS
  • R package

:: DOWNLOAD

 NRProF

:: MORE INFORMATION

Citation

Hari Krishna Yalamanchili, Quan-Wu Xiao, and Junwen Wang .
A novel neural response algorithm for protein function prediction
BMC Systems Biology 2012, 6(Suppl 1):S19

LightAssembler – Lightweight Resources Assembly Algorithm

LightAssembler

:: DESCRIPTION

LightAssembler is a lightweight assembly algorithm designed to be executed on a desktop machine. It uses a pair of cache oblivious Bloom filters, one holding a uniform sample of g-spaced sequenced k-mers and the other holding k-mers classified as likely correct, using a simple statistical test.

::DEVELOPER

Sara El-Metwally

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 LightAssembler

:: MORE INFORMATION

Citation

LightAssembler: fast and memory-efficient assembly algorithm for high-throughput sequencing reads.
El-Metwally S, Zakaria M, Hamza T.
Bioinformatics. 2016 Jul 13. pii: btw470.

CHIAMANTE 1.0.3 – Joint Genotype Calling algorithm for Array and Sequence data

CHIAMANTE 1.0.3

:: DESCRIPTION

Chiamante is a genotype caller for Illumina Beadchips that can augment microarray data with genotype likelihoods from sequence data for improved genotype accuracy and call rate. Whilst primarily designed to call genotypes via fusing these two sources of information, Chiamante also functions as a highly accurate array-only caller.

::DEVELOPER

Jared O’Connell and Jonathan Marchini.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 CHIAMANTE

:: MORE INFORMATION

Citation

J O’Connell, J. Marchini (2012)
Joint Genotype Calling With Array and Sequence Data.
Genetic Epidemiology. 10.1002/gepi.21657