BOL: Related items

BioRG

Tue, 04 Aug 2015 20:52:52 -0500

This research group works on problems from the fields of Bioinformatics, Biotechnology, Data Mining, and Information Retrieval. The group's research projects includes Comparative Genomics of Bacterial genomes, Metagenomics, Genomic databases, Pattern Discovery in sequences and structures, micro-array data analysis, prediction of regulatory elements, primer design, probe design, phylogenetic analysis, medical image processing, image analysis, data integration, data mining, information retrieval, knowledge discovery in electronic medical records, and more.

More at http://biorg.cis.fiu.edu/

HistoneDB 2.0 – with variants

Anjana — Fri, 03 Jun 2016 05:06:20 -0500

This histone database can be used to explore the diversity of histone proteins and their sequence variants in many organisms. The resource was established to better understand how sequence variation may affect functional and structural features of nucleosomes. To get started, select a histone type to explore its variants.

More at http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

BioDownloader

Surabhi Chaudhary — Sat, 25 Feb 2017 17:52:33 -0600

BioDownloader is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:

optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).
allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)
has a built-in repository containing the settings for the most common bioinformatics download needs
built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)
capable of performing multiple download or update tasks simultaneously

BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.

http://dunbrack.fccc.edu/BioDownloader/

Address of the bookmark: http://dunbrack.fccc.edu/BioDownloader/

NCBI Prokaryotic Genome Annotation Pipeline

Jit — Tue, 16 May 2017 08:56:03 -0500

NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).

Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.

NCBI has developed an automatic prokaryotic genome annotation pipeline that combines ab initio gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP; see Pubmed Article) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of the pipeline in NCBI Handbook chapter. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.

https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

Binding Site Prediction in Protein !

Poonam Mahapatra — Wed, 25 Apr 2018 04:35:57 -0500

The interaction between proteins and other molecules is fundamental to all biological functions. In this section we include tools that can assist in prediction of interaction sites on protein surface and tools for predicting the structure of the intermolecular complex formed between two or more molecules (docking).

Pockets Identification

CASTp

Automatic Identification of pockets and cavities in proteins structure, and quantitation of their volumes using Delaunay triangulation. Available also as PyMOL plugin

Pocket-Finder

Automatic identification of pockets and cavities in proteins structure, and quantitation of their volumes.

PocketPicker

Grid-based technique for the analysis of protein pockets. PocketPicker available as a plugin for PyMOL

Binding Site Prediction

ConSurf

Identification of functional regions in proteins by surface-mapping of phylogenetic information

CRESCENDO

Identification protein interaction sites. It uses sequence conservation patterns in homologous proteins to distinguish between residues that are conserved due to structural restraints from those due to functional restraints.

Ligand Binding Sites

3DLigandSite

The server utilizes protein-structure prediction to provide structural models of the binding site. Ligands bound to structures are superimposed onto the model and use to predict the binding site.

FINDSITE

A threading-based method for ligand-binding site prediction and functional annotation based on binding-site similarity across superimposed groups of threading templates.

LIGSITE^csc

Prediction of binding site by pocket identification using the Connolly surface and degree of conservation

metaPocketA meta server for ligand-binding site prediction. metaPocket use LIGSITE^csc, PASS, Q-SiteFinder and SURFNET

Research Associate Bioinformatics in IISc Recruitment 2020

Tue, 23 Jun 2020 21:53:34 -0500

Research Associate Bioinformatics in IISc Recruitment 2020

Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.

Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.

Desirable Qualifications (Research Associate/s): i) Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment).

ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv) Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.

The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.

Emoluments: As per DST, GOI norms and commensurate with experience.

More at https://www.iisc.ac.in/positions-open/

STRUM: structure-based prediction of protein stability changes upon single-point mutation

BioStar — Mon, 10 Sep 2018 13:21:49 -0500

STRUM is a method for predicting the fold stability change (ΔΔG) of protein molecules upon single-point nsSNP mutations. STRUM adopts a gradient boosting regression approch to train the Gibbs free-energy changes on a variety of features at different levels of sequence and structure properties. The unique characteristics of STRUM is the combination of sequence profiles with low-resolution structure models from protein structure prediction, which helps enhance the robustness and accuracy of the method and make it applicable to various protein seqences, including those without experimental structures

Address of the bookmark: https://zhanglab.ccmb.med.umich.edu/STRUM/

Scientists map 17,294 proteins produced in human body

Jit — Thu, 29 May 2014 01:57:55 -0500

Indian scientists missed the genomic profiling bus, but they've more than made up for it by creating the first human proteome map which is an extension of the genomic study. Till now, here is no direct equivalent for the human proteome. But recently two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome.

The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.

The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".

The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.

Reference:

http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html

http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme

http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.

https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB

Biology, Computers Collide in High-Demand Field of Bioinformatics

Mon, 25 Aug 2014 00:56:10 -0500

Dr. Shivas Amin calls bioinformatics a "collision of biology and computers." Students learn how to use computers and skills in math and biology to analyze genome and proteome projects to prepare for high-demand jobs in the life sciences. Learn more about Amin and hear from student Medina Baitemirova and alumnus Lukas Simon about the fast-growing field of bioinformatics.

Entrez Direct: E-utilities on the UNIX Command Line

Anjana — Wed, 19 Oct 2016 08:06:24 -0500

Entrez Direct (EDirect) is an advanced method for accessing the NCBI's suite of interconnected databases (publication, sequence, structure, gene, variation, expression, etc.) from a UNIX terminal window. Functions take search terms from command-line arguments. Individual operations are combined to build multi-step queries. Record retrieval and formatting normally complete the process.

EDirect also provides an argument-driven function that simplifies the extraction of data from document summaries or other results that are returned in structured XML format. This can eliminate the need for writing custom software to answer ad hoc questions. Queries can move seamlessly between EDirect commands and UNIX utilities or scripts to perform actions that cannot be accomplished entirely within Entrez.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/books/NBK179288/