Weight to Molar Quantity (for proteins)

For conversion of protein from weight to molar concentration. Here is the tool

Wolfram|Alpha: Future of search and analysis

This is something very interesting I came across recently. I have just seen the DEMO which is so mind blowing, actual site is located here Wolfram|Alpha. God!!! we are a growing species, I just have to say that it is just mind blowing....marvelous..yes we human ...mind is the speck over the hell to achieve unimaginable through the labyrinthine network of our neuronal circuit ..its evitable the more guttural pouch will emerge like this..which will be more useful in days to come...This is the future of the way we look at the internet today, the search we do over internet, The search results and their analysis, which otherwise takes us to 100s of pages with analysis for the required details over each page. Anyways, this Wolfram|Alpha looks so good and I am wondering that it came bit late. Very amazing piece of work, I am sure this is going to be very very useful to almost every internet user. I am also hopeful that as in comparison to the Google search results ,this gives more analyzed results. And no I am not comparing these two. Lots of mathematical calculation, lots of general work analysis. I am sure Wolfram|Alpha people are and will be having tough time maintaining such a brilliant technology.

miRex: A web based resource for miRNA expression profiles

Background: A few hundred miRNAs carry the potential to regulate thousands of target genes in eukaryotes. The expression profiles of miRNAs convey important information regarding tissue specific gene expression and can be used as a biomarker for disease progression and cancer classification among other rational interpretations pertaining to miRNA-gene interactions. There are several individual reports of miRNA expression profiling; however there is a lack of server that can render cross-comparison of all these datasets.

Description: We have developed miRex, a database and analysis tool for comparing miRNA expression profiles generated by high-throughput methods. Currently data from public repositories have been pre-normalized and provided with visual representation to aid comparison between experiments. miRNA ID converter: a tool for mapping miRNA IDs from one system of nomenclature to another has also been included.

Data: Currently, 614 experiments spanning 25 datasets deposited in Gene Expression Omnibus (GEO),the public repository for high-throughput gene expression data hosted by NCBI and 1132 experiments from 18 datasets from ArrayExpress, another resource for expression data, is available through miRex. Besides the microarray based data, there is a set of 40 experiments carried out by real time PCR.

URL: miRex is available at http://miracle.igib.res.in/mirex/

Reverse Complement

Reverse Complement

Reverse Complement is commonly used in Bioinformatics for various purposes. Here is the tool that does the job without much effort, there are simple Perl programs that could be run locally for the purpose. This tool is provided by GENE INFINITY, this can also do reverse and complementary separately. Hope this helps, the tool is located here, Reverse Complement

Protein Blast against another set of proteins

Protein Blast against another set of proteins

This tool is provided by NCBI/ BLAST/ blastp suite: BLASTP programs search protein databases using a protein query.This gives BLAST of a query protein against a set of other proteins. I found it useful when you don't wish to BLAST your query against whole protein database, instead a set of proteins given by the user. This tool is located here, Protein Blast against another set of proteins

PeptideCutter

PeptideCutter: http://expasy.org/tools/peptidecutter/

This tool is provided by ExPASy. This predicts potential cleavage sites cleaved by proteases or chemicals in a given protein sequence. 

PeptideCutter returns the query sequence with the possible cleavage sites mapped on it and /or a table of cleavage site positions. Single or multiple enzymes can be selected for the purpose. PeptideCutter

Predicting Antigenic Peptides

Predicting Antigenic Peptides

This is a program that predicts those segments from within a protein sequence that are likely to be antigenic by eliciting an antibody response. The method used here is the method of Kolaskar and Tongaonkar (1990). 

Predictions are based on a table that reflects the occurrence of amino acid residues in experimentally known segmental epitopes. Segments are only reported if the have a minimum size of 8 residues. The reported accuracy of method is about 75%. 

The program is located here Predicting Antigenic Peptides

Sequence analyzer

Sequence Massager: http://www.attotron.com/cybertory/analysis/seqMassager.htm

Nucleic Acid Sequence Massager is a very easy to use tool for convention of DNA to RNA, RNA to DNA, Upper Case to Lower Case and vice verse, Removal of FASTA format, Removal of HTML tags, Removal of number, White spaces, line breaks.

I find this tool very handy.

List of CSIR Institutes

Following is the list of CSIR Institutes for Life Science, Comprehensive list of the CSIR institutes can be downloaded from the link provided at the end of the list.

Center for Cellular & Molecular Biology

Central Drug Research Institute

Central Food Technological Research Institute

Central Institute of Medicinal and Aromatic Plants

Central Leather Research Institute

Institute of Genomics and Integrative Biology

Institute of Himalayan Bioresource Technology

Indian Institute of Chemical Biology

Indian Institute of Chemical Technology

Institute of Microbial Technology

Industrial Toxicology Research Center

National Botanical Research Institute

National Chemical Laboratory

National Environmental Engineering Research Institute

National Institute of Oceanography

National Institute of Science, Technology and Development Studies

National Physical Laboratory

Indian Institute of Integrative Medicine

National Institute for Interdisciplinary Science & Technology(NIST)

Predicting Subcellular Localization of Proteins

It is interesting to study the localization of proteins in subcellular due to several reasons. Here is a collection of the online available softwares that help in predicting subcellular localization of the proteins. Prediction is done with the help of programs which are trained for this purpose, this greatly helps in selection procedure, to select for a protein to work upon. Though there are more I have enlisted some commonly used.

CELLO : CELLO is a multi-class SVM classification system. CELLO uses 4 types of sequence coding schemes: the amino acid composition, the di-peptide composition, the partitioned amino acid composition and the sequence composition based on the physico-chemical properties of amino acids. We combine votes from these classifiers and use the jury votes to determine the final assignment. Yu CS, Lin CJ, Hwang JK: Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions. Protein Science 2004, 13:1402-1406.

PSORTb: Based on a study last performed in 2010, PSORTb v3.0.2 is the most precise bacterial localization prediction tool available. PSORTb v3.0.2 has a number of improvements over PSORTb v2.0.4. Version 2 of PSORTb is maintained here. You can currently submit one or more Gram-positive or Gram-negative bacterial sequences or archaeal sequences in FASTA format. Copy and paste your FASTA-formatted sequences into the textbox below or select a file containing your sequences to upload from your computer.

TMHMM Server: This server is for prediction of transmembrane helices in proteins. You can submit many proteins at once in one fasta file. Please limit each submission to at most 4000 proteins. Please tick the 'One line per protein' option. Please leave time between each large submission.S. Moller, M.D.R. Croning, R. Apweiler. Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics, 17(7):646-653, July 2001.

SignalP 3.0 Server: SignalP 3.0 server predicts the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms: Gram-positive prokaryotes, Gram-negative prokaryotes, and eukaryotes. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks and hidden Markov models. Locating proteins in the cell using TargetP, SignalP, and related tools Olof Emanuelsson, Søren Brunak, Gunnar von Heijne, Henrik Nielsen Nature Protocols 2, 953-971 (2007).

LOCtree: LOCtree can predict the subcellular localization and DNA-binding propensity of non-membrane proteins in non-plant and plant eukaryotes as well as prokaryotes. LOCtree classifies eukaryotic animal proteins into one of five subcellular classes, while plant proteins are classified into one of six classes and prokaryotic proteins are classified into one of three classes . The novel feature of using a hierarchical architecture is the ability to make intermediate localization class predictions at much higher accuracy's. Another source of improvement is the use of 'noisy' training data. 'Noisy' predictions from LOCKey (SWISS-PROT keyword based annotations) and LOCHom (annotations using sequence homology) are used to train the hierarchical SVMs.

PredictProtein: PredictProtein integrates feature prediction for secondary structure, solvent accessibility, transmembrane helices, globular regions, coiled-coil regions ,structural switch regions, B-values, disorder regions, intra-residue contacts, protein-protein and protein-DNA binding sites, sub-cellular localization, domain boundaries, beta-barrels, cysteine bonds, metal binding sites and disulphide bridges.