BOL: Related items

Demo 4: Using BLAST/BLAT in Ensembl

Tue, 10 Sep 2013 11:54:03 -0500

We demonstrate the BLAST/BLAT tool in Ensembl. Search for a sequence in Ensembl, and identify hits to the genome, or to genes, with this tool.

Evolution and Cancer

Fri, 27 Sep 2013 11:28:49 -0500

Air date: Wednesday, January 04, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Category: Wednesday Afternoon Lectures Description: There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Dr. David Botstein, Princeton University Runtime: 00:59:58 Permanent link: http://videocast.nih.gov/launch.asp?17046

Converting BLAST output into CSV

Poonam Mahapatra — Mon, 11 Dec 2017 04:17:58 -0600

Suppose we wanted to do something with all this BLAST output. Generally, that’s the case - you want to retrieve all matches, or do a reciprocal BLAST, or something.

As with most programs that run on UNIX, the text output is in some specific format. If the program is popular enough, there will be one or more parsers written for that format – these are just utilities written to help you retrieve whatever information you are interested in from the output.

Let’s conclude this tutorial by converting the BLAST output in out.txt into a spreadsheet format, using a Python script.

First, we need to get the script. We’ll do that using the ‘git’ program:

git clone https://github.com/ngs-docs/ngs-scripts.git /root/ngs-scripts

We’ll discuss ‘git’ more later; for now, just think of it as a way to get ahold of a particular set of files. In this case, we’ve placed the files in /root/ngs-scripts/, and you’re looking to run the script blast/blast-to-csv.py using Python:

python /root/ngs-scripts/blast/blast-to-csv.py out.txt

This outputs a spread-sheet like list of names and e-values. To save this to a file, do:

python /root/ngs-scripts/blast/blast-to-csv.py out.txt > ~out.csv

If you have Excel installed, try double clicking on it.

Pre- or postdoctoral research fellowship in Structural Bioinformatics in Padova

Wed, 02 Oct 2013 15:12:22 -0500

University of Padova (URL: http://protein.bio.unipd.it/)

A research fellowship is available at the BioComputing Laboratory, University of Padova (URL: http://protein.bio.unipd.it/). A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures. The BioComputing Laboratory is a group of a dozen people working on several aspects of prediction of protein structure & function employing techniques at the intersection between biology, medicine, chemistry, physics & computer science. Our aim is to integrate the development of novel methods and their application to biologically relevant problems. We are looking for candidates with a solid Bioinformatics background, programming experience (Python, Perl, C++ and/or Java) and good knowledge of molecular biology (protein structure/function, signalling pathways). Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial. The fellowship, which should start in late 2013, is initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be located at the BioComputing Laboratory, University of Padova. Travel support for conferences and/or research visits abroad may be provided. To apply, please send your CV, a brief description of your research background and the names of two (or more) references to Prof. Silvio Tosatto (Email: silvio.tosatto@unipd.it).

Contact Person (Referent): Silvio Tosatto
Ref. E-Mail: silvio.tosatto@unipd.it
Tel: +39 049 827 6269
Fax: +39 049 827 6260
Group Web Page: http://protein.bio.unipd.it/

Contract Faculty-Bioinformatics at Maulana Azad National Institute of Technology

Thu, 12 Dec 2013 20:46:52 -0600

Contract Faculty-Bioinformatics at Maulana Azad National Institute of Technology

Job Description:F.No.11/10(1)/929 Qualifications: Candidates should have Ph.D. degree. If Ph.D. candidates are not available at least Post Graduate degree with GATE/NET qualification is a must. Walk-in-Interview on 19.12.2013 at 2.30 P.M. to 5.30 P.M .. at Maulana Azad National Institute of Technology: Bhopal For more details,please visit website:http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf

For more @ http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf

Web address @ :http://www.manit.ac.in

BLAST+ 2.11.0 release is now available on FTP site !

Jit — Sat, 14 Nov 2020 21:37:53 -0600

BLAST+ 2.11.0 release is now available from our FTP site. The main advance is the ability to provide usage reports to NCBI to help us improve BLAST. This information is limited to the name of the BLAST program, some basic database metadata, a few BLAST parameters, as well the number and total size of your queries. See the Privacy document for more details on the information we collect, how we will use it, and how you can opt-out of reporting.

Another new feature allows threading by query batch in rpsblast/rpstblastn. Enabling this option using -m t provides more efficient searching with large numbers of queries. See release notes for details on more improvements and bug fixes.

Useful Links
------------
NCBI Insights: https://ncbiinsights.ncbi.nlm.nih.gov/2020/11/12/blast-2-11-0/

BLAST FTP: https://go.usa.gov/x7QQ3
Privacy document: https://go.usa.gov/x7QQe
Release notes: https://go.usa.gov/x7Qnv

Yau Group

Tue, 15 Oct 2013 13:05:15 -0500

Yau Group are a new research group based at the Wellcome Trust Centre for Human Genetics and the Department of Statistics at the University of Oxford.

Yau Group develops statistical and computational methods for the analysis of genomic datasets with a particular interest in cancer sequencing applications and the use of Bayesian Statistics.

Yau Group are currently have projects in somatic mutation analysis of heterogeneous cancers, data fusion or integration techniques and single cell genomics.

More @ http://www.well.ox.ac.uk/~cyau/index.html

Basics of BLAST Programs !

BioStar — Fri, 26 Jul 2024 06:04:26 -0500

The Basic Local Alignment Search Tool (BLAST) is a powerful bioinformatics program used to compare an input sequence (such as DNA, RNA, or protein sequences) against a database of sequences to find regions of similarity. Developed by the National Center for Biotechnology Information (NCBI), BLAST is widely used for identifying species, finding functional and evolutionary relationships between sequences, and predicting the function of novel sequences.

Key Features of BLAST:
1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.

2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.

3. Versatility: There are several versions of BLAST for different types of sequence comparisons:
- blastn: Compares a nucleotide query sequence against a nucleotide sequence database.
- blastp: Compares a protein query sequence against a protein sequence database.
- blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.
- tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.
- tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.

4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.

5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.

Applications of BLAST:
- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.
- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.
- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.
- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.

Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.

Associate Professor - Centre for Bioinformatics at Maharshi Dayanand University, Rohtak

Thu, 12 Dec 2013 20:49:59 -0600

ADVERTISEMENT No. PR-54/2013

No. of Posts and Specialization: 1(UR)

Educational Qualification:

(i) Good academic record with a Ph.D. Degree in the concerned /allied /relevant disciplines.

(ii) The Ph.D. Degree shall be a mandatory qualification for all candidates to be appointed as Associate Professor through direct recruitment.

(iii) A Master‟s Degree with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed).

(iv) A minimum of eight years of experience of teaching and /or research in an academic /research position equivalent to that of Assistant Professor in a University, College or Accredited Research Institution/Industry excluding the period of Ph.D research with evidence of published work and a minimum of 5 publications as books and /or research papers in refereed journals only/policy papers.

(v) Contribution to educations innovation, design of new curricula and courses and technology-mediated teaching learning process with evidence of having guided doctoral candidates and research students.

(vi) A minimum score as stipulated in the Academic Performance Indicator (API) based performance Based Appraisal System (PBAS), set out in this notification in as mentioned in the advertisement.

Send your application to the A.R (Estt.Teaching), M.D.University, Rohtak on or before December 23, 2013.

For more details: http://www.mdurohtak.ac.in/pdf/Notices_Pdf/new_notice/Teaching%20Vacancy%20%28ADVT.%20No.%20PR-54%20of%202013%29.pdf

Last Apply Date: 23 Dec 2013

RepeatMasker compatible blast tool

Neel — Fri, 07 Dec 2018 08:13:03 -0600

RMBlast is a RepeatMasker compatible version of the standard NCBI blastn program. The primary difference between this distribution and the NCBI distribution is the addition of a new program "rmblastn" for use with RepeatMasker and RepeatModeler.

RMBlast supports RepeatMasker searches by adding a few necessary features to the stock NCBI blastn program. These include:

Support for custom matrices ( without KA-Statistics ).
Support for cross_match-like complexity adjusted scoring. Cross_match is Phil Green's seeded smith-waterman search algorithm.
Support for cross_match-like masklevel filtering.

https://anaconda.org/bioconda/rmblast

Address of the bookmark: http://www.repeatmasker.org/RMBlast.html