ECC – Classification of Cells or other Biological Objects

ECC

:: DESCRIPTION

ECC (Enhanced CellClassifier) empowers the user with machine learning tools for classification of cells or other biological objects. If basic image analysis has already been completed by CellProfiler, ECC will calculate a model, apply and iteratively improve the model and analyse a whole plate or a set of plates. By doing this, complex image analysis tasks an be solved efficiently.

::DEVELOPER

 Lab of Prof. Wolf Dietrich Hardt

:: SCREENSHOTS

ecc

::REQUIREMENTS

  • Windows/Linux/MacOsX
  • matlab

:: DOWNLOAD

 ECC

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2010 Jan 14;11:30. doi: 10.1186/1471-2105-11-30.
Enhanced CellClassifier: a multi-class classification tool for microscopy images.
Misselwitz B, Strittmatter G, Periaswamy B, Schlumberger MC, Rout S, Horvath P, Kozak K, Hardt WD.

InforBIO 5.28 – E-Workbench for Databasing, Classification & Identification of Microbes

InforBIO 5.28

:: DESCRIPTION

InforBIO is an e-Workbench for databasing, classification and identification of microbes. InforBIO can identify the phenotypic characteristics that discriminate and are associated with the clusters of a phylogenetic tree.

::DEVELOPER

WFCC-MIRCEN World Data Centre for Microorganisms

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

 InforBIO

:: MORE INFORMATION

Citation

Hideaki Sugawara, Naoto Tanaka, and Satoru Miyazaki (2003)
An e-Workbench for the study of microbial diversity,
The system design and basic functions. Microbial. Cult. Coll., 19, 59-67 (InforBIO.pdf)

K-Pax – Bayesian unsupervised Classification of Protein Sequences

K-Pax

:: DESCRIPTION

K-Pax contains an implementation of a Bayesian model-based method for simultaneously classifying aligned proteins into functionally divergent subgroups and identifying their function specific residues

::DEVELOPER

Bayesian Statistics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 K-Pax

:: MORE INFORMATION

Citation:

Marttinen, P., Corander, J., Törönen, P. and Holm, L. (2006).
Bayesian search of functionally divergent protein subgroups and their function specific residues.
Bioinformatics, 22, 2466-2474.

SSPred – Identification & Classification of Proteins involved in Bacterial Secretion Systems

SSPred

:: DESCRIPTION

SSPred is a prediction server for the identification & classification of proteins involved in bacterial secretion systems

::DEVELOPER

Sachin Pundhir

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Server

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Pundhir, S., and Kumar, A. (2011)
SSPred: a prediction server based on SVM for the identification and classification of proteins involved in bacterial secretion systems.
Bioinformation 6(10): 380-382

RetroPred – Prediction, Classification and Extraction of non-LTR Retrotransposons

RetroPred

:: DESCRIPTION

The tool “Retropred” develped is an automated methods integrating results from PALS, PILER, MEME and artificial neural network (ANN). The pipeline allows rapid detection of genomic repeats and their further assignment as LINEs and SINEs based on conserve pattern.Pals and Piler are used to identify transposable DNA family.Then MEME is run to discover conserved short patterns (50 bp long) present in the identified repeats. From the discovered patterns, binary pattern files are generated.These patterns files are used as input for a trained Artificial Neural Network for classification into LINEs and SINEs. The results are parsed into graphical representation, indicating the location of LINEs and SINEs in the genome. By clicking the corresponding label it is possible to extract the repeat sequence.

::DEVELOPER

RetroPred Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 RetroPred

:: MORE INFORMATION

Citation

Pradeep K. Naik, Vinay K. Mittal and Sumit Gupta (2008).
RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs and SINEs) from the genome by integrating PALS, PILER, MEME and ANN.
Bioinformation 2(6): 263-270.

TpPred – Prediction and Classification of Transport proteins

TpPred

:: DESCRIPTION

TpPred  is an Artificial Neural Network (NN) based tool for prediction and classification of transport protein into its classes and sub-classes. It performs a 3 layer classification for transport proteins. The 1st layer of the prediction engine is for identifying a query protein as transport protein or not; the 2nd layer for the main functional class; and the 3rd layer for the sub-functional class.

::DEVELOPER

TpPred Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux /MacOsX
  • Java
  • EMBOSS 
  • Perl

:: DOWNLOAD

 TpPred

:: MORE INFORMATION

Citation

Sankalp Jain, Piyush Ranjan, Dipankar Sengupta and Pradeep K. Naik (2011).
TpPred: A tool for hierarchical prediction of transport proteins using cluster of neural networks and sequence derived features.
International Journal for Computational Biology, 0003:44-58, 2012.

ProClassify 1.4.2 – Proteomic data Classification

ProClassify 1.4.2

:: DESCRIPTION

 ProClassify is a tool for proteomic data classification. It was intended originally for high-resolution mass-spectrometry data classification, but it can be of use for datasets of a completely different nature as well.

::DEVELOPER

Genomics & Bioinformatics Graz, Graz University of Technology

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

 ProClassify 

:: MORE INFORMATION

Citation

Yu J.S.,Ongarello S., Fiedler R., Chen X.W., Toffolo G., Cobelli C., Trajanoski Z.
Ovarian Cancer Identification Based on Dimensionality Reduction for High-Througput Mass Spectrometry Data.
Bioinformatics 2005;21:2200-2209

Decision Forest 2 – Novel Pattern Recognition method for multiclass Classification in Microarray data analysis

Decision Forest 2

:: DESCRIPTION

Decision Forest is a novel pattern-recognition method for analysis of data from microarray experiments, proteomics research, and predictive toxicology

::DEVELOPER

the National Center for Toxicological Research (NCTR).

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Java

:: DOWNLOAD

  Decision Forest

:: MORE INFORMATION

Citation

Multiclass Decision Forest–a novel pattern recognition method for multiclass classification in microarray data analysis.
Hong H, Tong W, Perkins R, Fang H, Xie Q, Shi L.
DNA Cell Biol. 2004 Oct;23(10):685-94.

 

MDCS – Microarray Data Classification Server

MDCS

:: DESCRIPTION

The MDCS provides maximal margin Linear Programming method (Antonov et al., 2004) for classification of tumor samples based on microarray data. This procedure detects groups of genes and constructs models (features) that strongly correlate with particular tumor types. The detected features include genes whose functional relations are changed for particular cancer types.

::DEVELOPER

MDCS Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 MDCS

:: MORE INFORMATION

Citation:

Antonov, A.V., Tetko, I.V, Prokopenko, V.V., Kosykh,D. & Mewes, H.W.
Web Portal for Classification of Expression Data using Maximal Margin Linear Programming,
Bioinformatics, 2004, 20, 3284-5.

 

MICE 1.4 – Mouse Information & Classification Entity

MICE 1.4

:: DESCRIPTION

MICE (Mouse Information and Classification Entity) is a program aimed at facilitating the monitoring of animals in their facility. It consists of a virtual facility in which scientists can perform all the tasks done in the real world (i.e., receiving animals, breeding, etc…). Each animal is recorded with all associated information (birth date, cage number, ID number, tail analysis number, parents, genetic status, genetic background and more), allowing for reliable tracking. Animals can be identified, grouped, sorted, moved…, according to any parameter of interest to the scientist, including associated comments. Crossings are automatically processed by the program, which determines the new genetic background, generation number, cage location and due date.

MICE reminds the user when births are expected, and entering the newborn animals only requires a few clicks (of the mouse!). The genealogy of each animal can be determined in two different ways, including a visual tree from which each ancestor’s information can be retrieved.

::DEVELOPER

P. Pognonec

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Mac OsX

:: DOWNLOAD

MICE for Win ; for Mac

:: MORE INFORMATION

Citation:

MICE, a program to track and monitor animals in animal facilities. BMC Genetics 2001 Mar;2(1):4

Any comment and/or proposal concerning this application is welcome! Please contact P. Pognonec for additional information.