Tag: Gene Expression

Gene Expression 1.0.18 – Simulation of Gene Expression

Gene Expression 1.0.18

:: DESCRIPTION

Gene Expression expresses yourself through your genes! See if you can generate and collect three types of protein, then move on to explore the factors that affect protein synthesis in a cell.

::DEVELOPER

the PhET™ project at the University of Colorado

:: SCREENSHOTS

GeneExpression

:: REQUIREMENTS

  • Windows / Mac OsX / Linux
  • Java

:: DOWNLOAD

 Gene Expression

:: MORE INFORMATION

Citation

Science. 2008 Oct 31;322(5902):682-3. doi: 10.1126/science.1161948.
PHYSICS. PhET: simulations that enhance learning.
Wieman CE, Adams WK, Perkins KK.

GENECLUST 1.0.2 – Exploratory Analysis of Gene Expression Microarray data

GENECLUST 1.0.2

:: DESCRIPTION

GeneClust is a piece of computer software which can be used as a tool for exploratory analysis of gene expression microarray data. The development of GeneClust was motivated by surging interest to search for interpretable biological structure in gene expression microarray data.

::DEVELOPER

Kim-Anh Do, Ph.D.

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 GENECLUST

:: MORE INFORMATION

Citation

Cancer Inform. 2007;5:25-43. Epub 2007 Apr 2.
Application of gene shaving and mixture models to cluster microarray gene expression data.
Do KA, McLachlan GJ, Bean R, Wen S.

Voronto – Mapping Gene Expression to Ontologies with Voronoi Tessellations

Voronto

:: DESCRIPTION

Voronto is a tool that integrates expression data and biological ontologies, allowing the analyst to explore the whole ontology and detect changes on expression patterns inside the ontology.

::DEVELOPER

RODRIGO SANTAMARÍA

:: SCREENSHOTS

Voronto

:: REQUIREMENTS

  • Windows / Linux/MacOS
  • Java

:: DOWNLOAD

 Voronto

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Sep 1;28(17):2281-2. doi: 10.1093/bioinformatics/bts428. Epub 2012 Jul 4.
Voronto: mapper for expression data to ontologies.
Santamaría R1, Pierre P.

OncodriveCIS 1.1.0 – Assesses the Influence of Copy Number Alterations (CNA) in the Gene Expression

OncodriveCIS 1.1.0

:: DESCRIPTION

OncodriveCIS  is a method to identify genes that accumulate copy number alterations important for tumour development. This is done by computing the functional impact of CNAs by measuring their effect on the expression of the genes affected.

::DEVELOPER

 The Biomedical Genomics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Python

:: DOWNLOAD

 OncodriveCIS

:: MORE INFORMATION

Citation

Tamborero D, Lopez-Bigas N and Gonzalez-Perez A.
Oncodrive-CIS: a method to reveal likely driver genes based on the impact of their copy number changes on expression.
PLoS ONE 8(2): e55489. doi:10.1371/journal.pone.0055489

Simulac – Simulator for Complex Gene Expression Circuits

Simulac

:: DESCRIPTION

Simulac is an old but flexible simulator for complex gene expression circuits. Used initially to model complex promoter, elongation, and expression dynamics of the bacteriophage lambda lysis/lysogeny switch.

::DEVELOPER

The Arkin laboratory 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /Windows/ MacOsX
  • C Compiler

:: DOWNLOAD

 Simulac

:: MORE INFORMATION

APPEX 1.0 – Analysis Platform for Identification of Prognostic Gene EXpression Signature in Cancer

APPEX 1.0

:: DESCRIPTION

APPEX is a web-based platform to perform survival analysis, particularly, to support identifying molecular signatures significantly associated with cancer patients’ outcome. APPEX provides various analysis methods to discover genes or any other molecules associated with survival of cancer patients.

::DEVELOPER

Medical Genomics Research Center, KRIBB, Korea.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

APPEX: analysis platform for the identification of prognostic gene expression signatures in cancer.
Kim SK, Kim JH, Yun SJ, Kim WJ, Kim SY.
Bioinformatics. 2014 Aug 4. pii: btu521.

MiningABs 1.0.0 – Mining Associated Biomarkers across multi-connected Gene Expression datasets

MiningABs 1.0.0

:: DESCRIPTION

MiningABs is a new meta-analysis approach  to mine associated biomarkers (ABs) across different array-based datasets.

::DEVELOPER

frazer Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

 MiningABs

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2014 Jun 8;15:173. doi: 10.1186/1471-2105-15-173.
MiningABs: mining associated biomarkers across multi-connected gene expression datasets.
Cheng CP, DeBoever C, Frazer KA1, Liu YC, Tseng VS.

pGQL – Analyzing Gene Expression Time Courses

pGQL

:: DESCRIPTION

pGQL (probabilistic Graphical Query Language) is a software tool in particular for analyzing gene expression time courses. It allows its user to interactively define linear HMM queries on time course data using rectangular graphical widgets called probabilistic time boxes. The analysis is fully interactive and the graphical display shows the time courses along with the graphical query. The results can be submitted to gPROF directly from pGQL.

::DEVELOPER

Schliep lab

:: SCREENSHOTS

pGQL

:: REQUIREMENTS

  • Linux/ MacOsX/ Windows
  • Python

:: DOWNLOAD

  pGQL

:: MORE INFORMATION

Citation

BioData Min. 2011 Apr 18;4:9. doi: 10.1186/1756-0381-4-9.
pGQL: A probabilistic graphical query language for gene expression time courses.
Schilling R, Costa IG, Schliep A.

CellMix 1.6.2 – Gene Expression Deconvolution

CellMix 1.6.2

:: DESCRIPTION

CellMix , an R package that incorporates most state-of-the-art deconvolution methods, into an intuitive and extendible framework, providing a single entry point to explore, assess and disentangle gene expression data from heterogeneous samples.

::DEVELOPER

The UCT Computational Biology Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX/ Windows
  • R package

:: DOWNLOAD

 CellMix

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Sep 1;29(17):2211-2. doi: 10.1093/bioinformatics/btt351. Epub 2013 Jul 3.
CellMix: a comprehensive toolbox for gene expression deconvolution.
Gaujoux R1, Seoighe C.

novoSpaRc 0.4.3 – de novo Spatial Reconstruction of Single-Cell Gene Expression

novoSpaRc 0.4.3

:: DESCRIPTION

novoSpaRc predicts locations of single cells in space by solely using single-cell RNA sequencing data.

::DEVELOPER

N. Rajewsky Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

novoSpaRc

:: MORE INFORMATION

Citation

Moriel N, Senel E, Friedman N, Rajewsky N, Karaiskos N, Nitzan M.
NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport.
Nat Protoc. 2021 Sep;16(9):4177-4200. doi: 10.1038/s41596-021-00573-7. Epub 2021 Aug 4. PMID: 34349282.