BOL: Related items

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.

Generate interactive codon usage plots

Jit — Wed, 28 Feb 2018 03:47:40 -0600

Generate interactive codon usage plots as used at ensembl.lepbase.org. The input file format can be generated from an Ensembl database using the export_json.pl script from the easy-import pipeline.

live demo

Address of the bookmark: https://github.com/rjchallis/codon-usage

analyzing codon usage

Neel — Thu, 07 Nov 2019 08:31:05 -0600

perl script analyzing codon usage in an input sequence to evaluate how efficiently it will be expressed in Anopheles gambiae. The input codon usage table derived from highly‐expressed A. gambiae genes is appended below.

dcGOR

Martin Jones — Sat, 08 Nov 2014 14:54:28 -0600

An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.

The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:

1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html

2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html

3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html

OrthoANI: An improved algorithm and software for calculating average nucleotide identity

Abhimanyu Singh — Wed, 12 Dec 2018 08:36:08 -0600

OAT uses OrthoANI to measure the overall similarity between two genome sequences. ANI and OrthoANI are comparable algorithms: they share the same species demarcation cut-off at 95~96% and large comparison studies have demonstrated both algorithms to produce near identical reciprocal similarities. Details of the OrthoANI algorithm is given in (Lee et al. 2015). OAT employs an easy-to-follow Graphical User Interface that allow researchers to calculate OrthoANI values between genomes of interest without unfamiliar Command Line Environments. Moreover, the OAT_cmd command-line software can be integrated into preexisting bioinformatics pipelines.

Address of the bookmark: https://www.ezbiocloud.net/tools/orthoani

CRBHits: From Conditional Reciprocal Best Hits to Codon Alignments and Ka/Ks in R

Shruti Paniwala — Wed, 11 Nov 2020 23:06:03 -0600

CRBHits is a coding sequence (CDS) analysis pipeline in R (R Core Team, 2019). It reimplements the Conditional Reciprocal Best Hit (CRBH) algorithm crb-blast and covers all necessary steps from sequence similarity searches, codon alignments to Ka/Ks calculations and synteny. The new R package targets ecology, population and evolutionary biologists working in the field of comparative genomics.

Address of the bookmark: https://gitlab.gwdg.de/mpievolbio-it/crbhits

PHD SCHOLARSHIP DENMARK

Fri, 13 Jun 2014 13:44:07 -0500

ne PhD position is available at the Bioinformatics Center, Department of Biology, University of Copenhagen, Denmark. The PhD position concerns protein structure prediction, and will be in the Structural Bioinformatics group of Associate professor Thomas Hamelryck. The group is an integrated part of the Bioinformatics Center, which is headed by Professor Anders Krogh, employs around sixty scientists (including PhD students) and focuses on non-coding RNA, eukaryotic gene regulation and protein structure prediction. The center provides a modern, pleasant, international working environment with excellent modern facilities, in the heart of Copenhagen.
The project will be supervised by Associate Professor Thomas Hamelryck.

The protein folding problem is of enormous practical, theoretical and medical importance - and in addition forms a fascinating intellectual challenge. The aim of this project is to develop and implement a probabilistic method to infer the structure of proteins, building on various probabilistic models of protein structure developed by the Hamelryck group. The method will also take the dynamic nature of proteins into account, and involves a close collaboration with the statistics department at the university within the interdisciplinary project "Dynamical Systems: Mathematical Modeling and Statistical Methods for the Social, Health, and Natural Sciences" (http://dsin.ku.dk/).

Qualifications
Knowledge of programming (C++) and statistics or machine learning. Knowledge of biology, physics or biophysics is a plus, but not a requirement.

The deadline for applications is June 15, 2014

More at : https://job.jobnet.dk/CV/FindJob/details.aspx/3695051%20

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/

PhD student / Bio-informatician in computational protein modeling

Sun, 23 Feb 2020 03:46:46 -0600

PhD student / Bio-informatician in computational protein modeling
Job Profile
You will perform research on drug/protein interaction analysis in the context of lung cancer, using computational protein modeling. You will implement existing models predicting drug efficacy, related to EGFR-driven cancer. You will translate these models to novel oncogenes, including ROS1. You will validate these models against experimental data from a parallel project, with the final goal of deployment of your methods into clinical decision making. Your work will be embedded in an international network consisting of both academic partners and ROS1-NSCLC patient organizations.

Requirements

You are (or soon will be) a master in bio-informatics. You have strong ICT skills and you are eager to fully submerge into the world of protein modeling. You have good experience with Linux and one or more programming languages as well as knowledge of tertiary structure analysis. Candidates with a Master degree in one of the life sciences (Biomedical sciences, Biochemistry, Bio-engineering, Biostatistics, …), with relevant interest and extended experience in this field are also welcome. A general background cancer biology and genetics is needed. You are willing and eligible to apply for a personal PhD fellowship with the Flemish FWO (FWO.be). Therefore, it is required that you hold a master degree from a European university, and have not obtained your master diploma more than three years ago (see FWO website for detailed conditions). Proficiency in English, and good communication skills, both oral and written, are required. You are highly motivated, and you like to work in an interactive research team. You are willing to work on a 4-year PhD project starting beginning of 2020.

What we offer

We offer a one year position, as a PhD student, which can be extended up to 4 year upon positive evaluation, even if a personal fellowship application is not successful. Wages are according to the standard Flemish bursary levels for PhD students.

Interested?
For additional information please contact dr. Geert Vandeweyer. To apply, send a copy of your CV including details of your relevant skills and a motivation letter by e-mail to dr. Geert Vandeweyer (geert.vandeweyer@uantwerpen.be) before March 15, 2020.

Source:https://academicpositions.be/ad/university-of-antwerp/2020/phd-student-bio-informatician-in-computational-protein-modeling/141252?utm_source=jooble&utm_medium=cpc&utm_campaign=jooble

An entire genome written in lab

Rahul Nayak — Fri, 25 Oct 2013 09:43:03 -0500

This is the first time ever the genetic code has been fundamentally changed. The breakthrough is a huge step forward in synthetic biology and opens up the possibility of turning re-coded bacteria into biofactories, capable of producing potent new forms of protein that could fight disease or generate sustainable materials.

More @ http://news.yale.edu/2013/10/17/researchers-rewrite-entire-genome-and-add-healthy-twist

News Reference: Yale news

Image Source: Sciencedaily.