Tag: Time Series

DyNB 20150501 – Analyze RNA-seq Time Series data

DyNB 20150501

:: DESCRIPTION

DyNB is novel statistical methodology for analyzing time-course RNA-seq data.

::DEVELOPER

Computational systems biology group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Matlab

:: DOWNLOAD

 DyNB

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Jun 15;30(12):i113-20. doi: 10.1093/bioinformatics/btu274.
Methods for time series analysis of RNA-seq data with application to human Th17 cell differentiation.
Äijö T, Butty V, Chen Z, Salo V, Tripathi S, Burge CB, Lahesmaa R, Lähdesmäki H.

TiCoNE 2.0.0 – Cluster multi-patient-sample Time-series data

TiCoNE 2.0.0

:: DESCRIPTION

TiCoNE (Time Course Network Enricher) is a tool for the combined analysis of time series expression data together with biological networks.It will find time patterns emerging in the expression data and check for network modules enriched with genes of similar expression behavior over time.

::DEVELOPER

Baumbach lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Java
  • Cytoscape

:: DOWNLOAD

TiCoNE

:: MORE INFORMATION

Citation

Syst Med (New Rochelle). 2019 Mar 28;2(1):1-9. doi: 10.1089/sysm.2018.0013.
Time-Resolved Systems Medicine Reveals Viral Infection-Modulating Host Targets.
Wiwie C, Kuznetsova I, Mostafa A, Rauch A, Haakonsson A, Barrio-Hernandez I, Blagoev B, Mandrup S, Schmidt HHHW, Pleschka S, Röttger R, Baumbach J

MetATT – Metabolomics tool for Analyzing Two-factor and Time-series data

MetATT

:: DESCRIPTION

MetATT is a easy-to-use, web-based tool designed for time-series and two-factor metabolomics data analysis. MetATT offers a number of complementary approaches including 3D interactive principal component analysis, two-way heatmap visualization, two-way ANOVA, ANOVA-simultaneous component analysis and multivariate empirical Bayes time-series analysis.

::DEVELOPER

the Wishart Research Group, University of Alberta

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Java
  • R package
  • Apache Tomcat 6.0 or Glassfish v2/v3.

:: DOWNLOAD

  MetATT

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Sep 1;27(17):2455-6. doi: 10.1093/bioinformatics/btr392. Epub 2011 Jun 27.
MetATT: a web-based metabolomics tool for analyzing time-series and two-factor datasets.
Xia J, Sinelnikov IV, Wishart DS.

GeneShelf – Web-based Visual Interface for Large Gene Expression Time-series Data Repositories

GeneShelf

:: DESCRIPTION

GeneShelf builds upon a zoomable grid display to represent two categorical dimensions. It also incorporates an augmented timeline with expandable time points that better shows multiple data values for the focused time point by embedding bar charts. We applied GeneShelf to one of the largest microarray datasets generated to study the progression and recovery process of injuries at the spinal cord of mice and rats. There are also considerations of the analysis methods, and the entire data set was converted into three probe set algorithms (Plier, GC-RMA, and dChip), leading to nearly 10,000 microarray data files. SpinalCordLink can provide researchers with a good resource to interactively investigate one of the world largest microarray datasets.

::DEVELOPER

GeneShelf Team

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Java

:: DOWNLOAD

 GeneShelf

:: MORE INFORMATION

Citation

IEEE Trans Vis Comput Graph. 2009 Nov-Dec;15(6):905-12.
GeneShelf: a web-based visual interface for large gene expression time-series data repositories.
Kim B, Lee B, Knoblach S, Hoffman E, Seo J.

EDISA 1.0 – Extracting Biclusters from multiple Time-series of Gene Expression Profiles

EDISA 1.0

:: DESCRIPTION

EDISA (Extended Dimension Iterative Signature Algorithm) is a novel probabilistic clustering approach for 3D gene-condition-time datasets. Based on mathematical definitions of gene expression modules, the EDISA samples initial modules from the dataset which are then refined by removing genes and conditions until they comply with the module definition. A subsequent extension step ensures gene and condition maximality. We applied the algorithm to a synthetic dataset and were able to successfully recover the implanted modules over a range of background noise intensities.

EDISA Online Version

::DEVELOPER

the Center for Bioinformatics Tübingen (Zentrum für Bioinformatik Tübingen, ZBIT).

:: SCREENSHOTS

EDISA

:: REQUIREMENTS

  • Linux/ WIndows
  • Matlab

:: DOWNLOAD

  EDISA

:: MORE INFORMATION

Citation

Jochen Supper, Martin Strauch, Dierk Wanke, Klaus Harter, Andreas Zell:
EDISA: extracting biclusters from multiple time-series of gene expression profiles
BMC Bioinformatics 2007, 8:334

BTW 1.0 – Web Server for Gene Expression Time series Boltzmann Time Warping

BTW 1.0

:: DESCRIPTION

The BTW (Boltzmann Time Warping) web server allows a user to upload two tab-separated text files A,B of gene expression data, each possibly having a different number of time intervals of different durations. BTW then computes time warping distance between each gene of A with each gene of B, using a recently developed symmetric algorithm which additionally computes the Boltzmann partition function and outputs Boltzmann pair probabilities.

:: DEVELOPER

Clote Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Python

:: DOWNLOAD

 BTW

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W482-5.
BTW: a web server for Boltzmann time warping of gene expression time series.
Ferrè F, Clote P.