SAIC – Identify Significant Consensus Aberrations in Cancer Genome

SAIC

:: DESCRIPTION

SAIC (Significant Aberrations in Cancer) is a software to identify significant consensus aberrations in cancer genome.

::DEVELOPER

Computational Bioinformatics & Bio-imaging Laboratory (CBIL)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • C Compiler

:: DOWNLOAD

 SAIC

:: MORE INFORMATION

WordSpy 1.5 – Identify Transcription Factor Binding Motifs by building a dictionary and learning a grammar

WordSpy 1.5

:: DESCRIPTION

WordSpy is a novel, steganalysis-based approach for genome-wide motif finding. The software views regulatory regions as a stegoscript with cis-elements embedded in ‘background’ sequences. WordSpy can discover a complete set of cis-elements and facilitate the systematic study of regulatory networks.

::DEVELOPER

Computational Intelligence Center(CIC)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • Perl 

:: DOWNLOAD

  WordSpy

:: MORE INFORMATION

Citation:

Guandong Wang and Weixiong Zhang
A steganalysis-based approach for genome-wide identification of regulatory DNA sequence elements
Genome Biology 2006, 7:R49

 

tRNAcc 1.0 – Identify Genomic Islands Associated with tRNA Genes

tRNAcc 1.0

:: DESCRIPTION

tRNAcc is a tool for identifying genomic islands (novel gene content) associated with tRNA genes

::DEVELOPER

Hong-Yu Ou (tjohy@hotmail.com) , Kumar Rajakumar ( kr46@le.ac.uk)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows

:: DOWNLOAD

 tRNAcc

:: MORE INFORMATION

Citation:

Nucleic Acids Res. 2006 Jan 9;34(1):e3.
A novel strategy for the identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites in closely related bacteria.
Ou HY, Chen LL, Lonnen J, Chaudhuri RR, Thani AB, Smith R, Garton NJ, Hinton J, Pallen M, Barer MR, Rajakumar K.

WHICHLOCI 1.0 – Use Genotype data to Identify the loci most useful for Population Assignment

WHICHLOCI 1.0

:: DESCRIPTION

WHICHLOCI concerns these individual based population assignment methods but presents the method looking back on itself. Trial assignments with loci one at a time allows ranking of loci in terms of their efficiency for correct population assignment and conversely their propensity to cause false assignments. Subsequent trials with increasing numbers of loci determines what minimum number of which specific loci is required in order to attain defined power for population assignment.

::DEVELOPER

BODEGA MARINE LABORATORY

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 WHICHLOCI

:: MORE INFORMATION

Citation:

Bioinformatics. 2003 Jul 22;19(11):1436-8.
Which genetic loci have greater population assignment power?
Banks MA, Eichert W, Olsen JB.

freqAnalysis – Identify Statistically Aberrant k-length Nucleotide Motifs in coding DNA sequences

freqAnalysis

:: DESCRIPTION

freqAnalysis was designed to identify statistically aberrant k-length nucleotide motifs in coding DNA sequences, specifically to identify putative programmed translational frameshift sites. These are short sequences capable of inducing highly efficient ribosomal frameshifting by destabilizing normal ribosome-mRNA interaction. Because of the potentially catastrophic effect of frameshifting on normal protein production, we reasoned, such sites would be selected against by evolution and hence statistically underrepresented in protein-encoding sequences.

::DEVELOPER

Gesteland & Atkins Labs

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/windows/MacOsX
  • Java

:: DOWNLOAD

 freqAnalysis

:: MORE INFORMATION

Citation

Bioinformatics. 2002 Aug;18(8):1046-53.
Computational identification of putative programmed translational frameshift sites.
Shah AA, Giddings MC, Parvaz JB, Gesteland RF, Atkins JF, Ivanov IP.

ml-SVR – Identify Condition-Specific Regulatory Networks

ml-SVR

:: DESCRIPTION

ml-SVR (Multi-level Support Vector Regression) implements regulatory module identification through multi-level support vector regression

::DEVELOPER

Computational Bioinformatics & Bio-imaging Laboratory (CBIL)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 ml-SVR

:: MORE INFORMATION

Citation:

Bioinformatics. 2010 Jun 1;26(11):1416-22. Epub 2010 Apr 7.
Multilevel support vector regression analysis to identify condition-specific regulatory networks.
Chen L, Xuan J, Riggins RB, Wang Y, Hoffman EP, Clarke R.

COCO-CL – Identify Orthologous set of Genes.

COCO-CL

:: DESCRIPTION

COCO-CL (COrrelation COefficient-based CLustering) is a software for hierarchical clustering of orthology/homology relations, and identificationof orthologous groups of genes.

::DEVELOPER

Raja Jothi

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • perl 

:: DOWNLOAD

 COCO-CL

:: MORE INFORMATION

Citation

Raja Jothi, et al
COCO-CL: Hierarchical Clustering of Homology Relations Based on Evolutionary Correlations
Bioinformatics. 2006 April 1; 22(7): 779–788.

EPIG – Extract Microarray Gene Expression Patterns and Identifying co-expressed Genes

EPIG

:: DESCRIPTION

EPIG (Extracting Patterns and Identifying co-expressed Genes) is a method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes. Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratios, EPIG extracts a set of patterns representing co-expressed genes without a pre-defined seeding of the patterns.

::DEVELOPER

Clarice R. Weinberg, Ph.D.

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows /MacOsX
  • Java 

:: DOWNLOAD

 EPIG 

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2007 Nov 2;8:427.
Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes.
Chou JW, Zhou T, Kaufmann WK, Paules RS, Bushel PR.

fdrMotif – Identify Cis-elements by an EM Algorithm Coupled with False Discovery Rate Control

fdrMotif

:: DESCRIPTION

fdrMotif is iterative and alternates between updating the position weight matrix (PWM) and significance testing. It starts with an initial PWM and a set of sequences (e.g., from ChIP experiments). It generates many sets of background (null) sequences under the input sequence probability model. At each model estimation step, fdrMotif determines the number of binding sites in each sequence by performing statistical tests. The FDR in the original dataset is controlled by monitoring the proportion of background subsequences that are declared as binding sites. The PWM is updated using an EM algorithm with two iterative steps (the E and M steps) until convergence. In the E-step, fdrMotif normalizes the sum of the probabilities over all position s in a sequence to the number of binding sites found in the sequence.

::DEVELOPER

Leping Li, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 fdrMotif

:: MORE INFORMATION

Citation:

Bioinformatics. 2008 Mar 1;24(5):629-36.
fdrMotif: identifying cis-elements by an EM algorithm coupled with false discovery rate control.
Li L, Bass RL, Liang Y.

DiNAMIC – Identify recurrent DNA copy number Aberrations in Tumors

DiNAMIC

:: DESCRIPTION

DiNAMIC (Discovering Copy Number Aberrations Manifested In Cancer) is a novel method for assessing the statistical significance of recurrent copy number aberrations. In contrast to competing procedures, the testing procedure underlying DiNAMIC is carefully motivated, and employs a novel cyclic permutation scheme. Extensive simulation studies show that DiNAMIC controls false positive discoveries in a variety of realistic scenarios.

::DEVELOPER

V. Walter, A.B. Nobel, and F.A. Wright

:: SCREENSHOTS

N/A

::REQUIREMENTS

:: DOWNLOAD

 DiNAMIC

:: MORE INFORMATION

Citation

V. Walter, A.B. Nobel, and F.A. Wright
DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors
Bioinformatics (2011) 27 (5): 678-685.