BOL: Related items

ANItools web: a web tool for fast genome comparison within multiple bacterial strains

Jit — Wed, 14 Nov 2018 04:34:23 -0600

ANItools is a software package written by PERL scripts that can be run in a Linux/Unix system. If you want to compare bacterial genomes and calculate their average nucleotide identity (ANI), you could download and run this program directly. Or you could send us the genome sequence by email. Then we will do the analysis work for you.

https://academic.oup.com/database/article/doi/10.1093/database/baw084/2630454

Address of the bookmark: http://ani.mypathogen.cn/

EFS: an ensemble feature selection tool implemented as R-package and web-application

Jit — Tue, 28 Jan 2020 05:12:23 -0600

The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble.

https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8

Address of the bookmark: http://efs.heiderlab.de/

SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology

Abhimanyu Singh — Tue, 23 May 2017 05:28:56 -0500

SIMBA, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7

Address of the bookmark: http://ufmg-simba.sourceforge.net/

List of cancer genomics research web resources !

biogeek — Wed, 27 Dec 2017 20:33:09 -0600

Major web resources for cancer genomics research

CGHub
https://cghub.ucsc.edu/
Comprehensive data repository; huge data size

EGA
https://www.ebi.ac.uk/ega/
Comprehensive data repository; huge data size

COSMIC
http://cancer.sanger.ac.uk
Largest somatic mutation database; genome sequencing paper curation

CPRG
http://www.broadinstitute.org/software/cprg
Interface for cancer program resources

GDAC
http://gdac.broadinstitute.org/
Data analysis; automatic pipelines; user-friendly reports

SNP500Cancer
http://snp500cancer.nci.nih.gov
Sequence and genotype verification of SNPs

canEvolve
www.canevolve.org/
Comprehensive analysis of tumor profile; Data from 90 studies involving more than 10,000 patients

MethyCancer
http://methycancer.psych.ac.cn
Relationship among DNA methylation, gene expression and cancer

SomamiR
http://compbio.uthsc.edu/SomamiR/
Correlation between somatic mutation and microRNA; genome-wide displaying

cBioPortal
http://www.cbioportal.org/public-portal/
Graphical summaries; gene alteration; processed data; visualization

UCSC Cancer Genomics Browser
https://genome-cancer.soe.ucsc.edu/
Clinical information; gene expression; copy number variation; visualization

CGWB
https://cgwb.nci.nih.gov/
Visualization; gene mutation and variation; automated analysis pipeline

GDSC
http://www.cancerrxgene.org
Drug sensitivity information; drug response information

canSAR
https://cansar.icr.ac.uk/
Multidisciplinary information; drug discovery

NONCODE
http://www.noncode.org/ ncRNAs;
lncRNAs; up-to-date and comprehensive resource

Predicting Pathogen Virulence Using Bioinformatics Tools

BioStar — Tue, 04 Nov 2025 07:55:53 -0600

In the genomic era, the ability to predict the virulence potential of pathogens has become an indispensable part of infectious disease research. With the exponential growth of microbial genome data, bioinformatics tools now enable scientists to identify virulence factors, model pathogen behavior, and even forecast outbreak risks — all from sequence data.

In an age where pathogens continue to evolve and cross boundaries, understanding what makes them virulent—that is, capable of causing disease—has become a critical focus in modern microbiology and genomics. Virulence prediction bridges computational biology, genomics, and machine learning to forecast the pathogenic potential of microbes before they strike.

What Is Virulence?

Virulence refers to the degree of damage a pathogen can inflict on its host. It is determined by a combination of genetic factors—called virulence factors (VFs)—that allow the organism to attach, invade, evade, and harm the host. These include genes coding for toxins, secretion systems, adhesins, and enzymes that disrupt host defenses.

Understanding virulence factors not only helps in deciphering the mechanisms of infection but also provides early warning signs for emerging threats.

Why Predict Virulence?

Traditional virulence studies relied heavily on experimental infection models, which, although accurate, are time-consuming, expensive, and ethically constrained.
Today, the availability of whole-genome sequences and large-scale pathogen databases has paved the way for in silico virulence prediction—a computational approach that can screen thousands of genomes within hours.

This approach enables researchers to:

Rapidly identify potential high-risk strains.
Prioritize pathogens for containment, surveillance, or further study.
Guide vaccine development and drug target discovery.
Support One Health frameworks, linking animal, human, and environmental health data.

How Is Virulence Predicted?

Virulence prediction combines bioinformatics pipelines with machine learning and comparative genomics. The process generally involves:

Genome Annotation: Identifying genes and coding sequences in microbial genomes.
Feature Extraction: Comparing sequences with curated databases like VFDB (Virulence Factor Database), PATRIC, or Victors.
Pattern Recognition: Using algorithms (e.g., Random Forest, SVM, or deep learning models) to classify genes or strains as virulent or non-virulent based on sequence patterns, motifs, and protein domains.
Scoring and Visualization: Assigning a virulence score or confidence level and visualizing it through heatmaps or genome maps.

Tools and Resources for Virulence Prediction

A number of tools and databases make virulence prediction accessible to the scientific community:

VFanalyzer – For identifying virulence genes based on VFDB.
PathoFact – Predicts virulence, antimicrobial resistance (AMR), and toxin genes from metagenomic data.
Pangenome-based models – Identify virulence-associated gene clusters across strains.
Machine learning models – Use features like GC content, codon usage bias, or protein domains to predict pathogenicity.

Emerging tools now integrate multi-omic data—including transcriptomics, proteomics, and metabolomics—to understand virulence in a systems biology framework.

Applications in the Real World

Virulence prediction has major implications across public health and research sectors:

Epidemic preparedness: Early identification of virulent strains in outbreak samples.
AMR surveillance: Linking virulence profiles with antibiotic resistance determinants.
Environmental monitoring: Predicting pathogenic potential of soil or waterborne microbes.
Clinical diagnostics: Supporting personalized treatment through pathogen profiling.

For instance, integrating virulence prediction pipelines into national surveillance networks could enable faster risk assessment and response to infectious outbreaks.

The Road Ahead

As machine learning and genomics advance, virulence prediction will evolve from simple gene-based detection to dynamic, context-aware models that account for host–pathogen interactions, environmental signals, and evolutionary adaptation.

Future tools may predict not just if a strain is virulent, but under what conditions it expresses that virulence—bridging the gap between genotype and phenotype.

In Summary

Virulence prediction is redefining how we understand and anticipate infectious diseases. By coupling genomic insights with computational intelligence, researchers can identify potential threats earlier, design smarter interventions, and ultimately, strengthen our preparedness against emerging pathogens.

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

Gblocks: eliminates poorly aligned positions and divergent regions of a DNA or protein alignment

Poonam Mahapatra — Sat, 02 Jun 2018 07:36:05 -0500

Gblocks eliminates poorly aligned positions and divergent regions of a DNA or protein alignment so that it becomes more suitable for phylogenetic analysis. This server implements the most important features of the Gblocks program to make its use as simple as possible without loosing the functionality that it is necessary in most of the cases. Other options can be changed in the stand-alone program. You can see here an example output file showing the blocks selected from a protein alignment. Further information can be found in the online documentation.

Address of the bookmark: http://molevol.cmima.csic.es/castresana/Gblocks_server.html

List of motif discovery tools !

Neel — Tue, 20 Nov 2018 03:54:26 -0600

In genetics, a sequence motif is a nucleotide or amino-acid sequence pattern that is widespread and has, or is conjectured to have, a biological significance. For proteins, a sequence motif is distinguished from a structural motif, a motif formed by the three-dimensional arrangement of amino acids which may not be adjacent.

Following are the list of tools for motif discovery:

2Dsweep -- protein annotation by secondary structure elements

Perform secondary structure predictions on protein sequences.

3D-footprint -- database of DNA-binding protein structures

Find binding specificity information about DNA-protein complexes.

3D-footprint: DNA-binding protein database

Find information about the binding specificity of DNA-binding proteins.

3D-partner -- a web server to infer interacting partners and binding models

Predict interacting partners and binding models.

3MOTIF -- a protein structure visualization system for conserved sequence motifs

Use this web-based sequence motif visualization system to display sequence motif information in its appropriate three-dimensional (3D) context.

AFAWE -- Automatic functional annotation in a distributed Web Services Environment

Protein function prediction and annotation in an integrated environment powered by web service.

ANCHOR -- Prediction of Protein Binding Regions in Disordered Proteins

Find information about protein binding.

ANNIE -- ANNotation and Interpretation Environment for Protein Sequences

Use to predict function from de novo protein sequences.

Active Sequences Collection (ASC) database -- A new tool to assign functions to protein sequences

Search for short active protein sequences with demonstrated biological activities.

Blocks -- Ungapped segments in conserved protein sequences

Search for ungapped segments corresponding to the most highly conserved regions of proteins.

CASTp -- computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues

Identify and measure surface accessible pockets as well as interior inaccessible cavities, for proteins and other molecules.

CSA -- The Catalytic Site Atlas

To search for catalytic residue annotation for enzymes in the Protein Data Bank.

ConFunc -- Conserved residue Protein Function Prediction Server

Predict protein function using Gene Ontology.

ConSurf-DB -- evolutionary conservation profiles of protein structures database

Automatically calculate evolutionary conservation scores of key amino acid residues and map them on protein structures.

DBAli -- A Database of Structure Alignments

Mine the protein structure space.

DILIMOT -- discovery of linear motifs in proteins

Predict short linear motifs (3-8 residues) in a set of protein sequences.

Dasty2 -- an Ajax protein DAS client

A web client for visualizing protein sequence feature information using DAS.

DomainSweep -- protein annotation by domain analysis

Identify the domain architecture within a protein sequence.

E1DS -- catalytic site prediction based on 1D signatures of concurrent conservation

Predict enzyme catalytic site.

ELM -- Eukarotic Linear Motif Resource

Predict functional sites in eukaryotic proteins.

EXPASY Proteome Tools Collection

Use a collection of tools for protein analyses.

EXPASY-Findmod

Predict potential protein post-translational modifications and find potential single amino acid substitutions in peptides.

EzCatDB -- the Enzyme Catalytic-mechanism Database

Search for information related to the catalytic mechanisms of enzymes.

FFPred -- feature-based function prediction

An integrated feature-based function prediction server for vertebrate proteomes.

FingerPRINT Scan

Identify the closest matching PRINTS sequence motif fingerprints in a protein sequence.

FireDB -- a database of functionally important residues from proteins of known structure

Search for functional annotation of important sites in proteins with known structures.

Frog2 -- a FRee Online druG 3D conformation generator

Produce 3D conformations of small drug compounds.

HGPD -- Human Gene and Protein Database

A database presenting experiment-based results in human proteomics.

HHsenser -- exhaustive transitive profile search using HMMx96HMM comparison

Conduct exhaustive intermediate profile searches of a set of homologous protein sequences.

HotSpot Wizard -- Substrate Specificity Hot Spot Identification web server

Design protein mutations in site-directed mutagenesis.

INTREPID -- INformation-theoretic TREe traversal for Protein functional site IDentification

Use for protein functional site identification.

Integrating protein annotation resources through the Distributed Annotation System

Annotate protein using this integrated annotation resource.

InterProScan -- protein domains identifier

Identify protein family (and DNA) domains, patterns, motifs, protein families, and functional sites.

KFC -- Knowledge-based FADE and Contacts

Interactive forecasting of protein interaction hot spots.

MAGIIC-PRO -- detecting functional signatures by efficient discovery of long patterns in protein sequences

Discover long patterns in protein sequences.

MALISAM -- Manual ALIgnments for Structurally Analogous Motifs

Database containing pairs of structural analogs and their alignments.

MEME -- discovering and analyzing DNA and protein sequence motifs

Find sequence patterns in DNA and protein sequences.

MODPROPEP -- a program for knowledge-based modeling of protein-peptide complexes

A web server for knowledge-based modeling of protein-peptide complexes, specifically peptides in complex with major histocompatibility complex (MHC) proteins and kinases.

MeMo -- a web tool for prediction of protein methylation modifications

Predict protein methylation sites.

MegaMotifBase -- a database of structural motifs in protein families and superfamilies

Find structural segments or motifs for protein structures.

Minimotif Miner -- a tool for investigating protein function

Find motifs in a protein sequence.

Motif3D -- Relating protein sequence motifs to 3D structure

Visualize protein sequence motifs on the 3D protein structures.

MotifScan

Find presence of any known protein motif (Prosite and Pfam) in a protein sequence.

MultiBind -- Multiple Alignment of Protein Binding Sites

Recognize spatial chemical binding patterns common to a set of protein structures.

NMT -- The MYR Predictor

Analyze proteins for the presence of N-terminal N-myristoylation site.

NetNGlyc -- N-Glycosylation sites prediction tool

Find the presence of N-Glycosylation sites in human proteins.

NetOGly 3.1 -- O-glycosylation sites prediction tool

Find the presence of O-GalNAc (mucin type) glycosylation sites in mammalian proteins.

NetPhos 2.0 -- Phosphorylation sites predictions

Analyze eukaryotic proteins for the presence of serine, threonine and tyrosine phosphorylation sites.

NetPhosK 1.0 Server -- kinase specific eukaryotic protein phosphorylation sites prediction tool

Find possible kinase specific phosphorylation sites in eukaryotic proteins.

NetworKIN -- a resource for exploring cellular phosphorylation networks

NeuroPred -- a tool to predict cleavage sites in neuropeptide precursors and provide the masses of the resulting peptides

Predict cleavage sites at basic amino acid locations in neuropeptide precursor sequences.

Non-Redundant Patent Sequences - Patented Sequence Database

Find information about patented nucleotide and protein sequences.

O-GLYCBASE

Search for information about glycoproteins with O-linked and C-linked glycosylation sites.

PANDORA -- Protein ANnotation Diagram ORiented Analysis

Find information about protein sequence annotations.

PAR-3D -- Protein Active site Residue - 3D structural motif

A server to predict protein active site residues.

PDBSite -- a database of the 3D structure of protein functional sites

Search for structural and functional information on the protein functional sites.

PDBSiteScan -- A program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins

Search 3D protein fragments similar in structure to known active, binding and posttranslational modification sites.

PEDANT -- Protein Extraction, Description and ANalysis Tool

Conduct genome wide functional and structural analysis.

PHOSIDA -- Phosphorylation site database

Search for phosphorylation data of any protein of interest.

PHOSPHORYLATION SITE DATABASE

Search for information on prokaryotic proteins that undergo serine, threonine, or tyrosine phosphorylation.

PNU -- Protein Naming Utility

Determine correct names for proteins.

POODLE-S -- Predicition Of Order and Disorder by machine LEarning

Web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.

PPISearch -- Protein-Protein Interaction Search

Find homologous protein-protein interactions across multiple species.

PPSearch

Search your query sequence against PROSITE pattern database for protein motifs.

PRIDB -- Protein-RNA Interface DataBase

Find information about protein-RNA complexes from the Protein Data Bank (PDB).

PRINTS and its automatic supplement, prePRINTS -- A compendium of protein fingerprints

Search for protein fingerprints.

PROSITE

Identify protein families and domains for a given protein sequence.

PRRDB -- Pattern Recognition Receptor Database

A comprehensive database of pattern-recognition receptors and their ligands.

PatMatch -- a program for finding patterns in peptide and nucleotide sequences

Search for short nucleotide or peptide sequences such as cis-elements in nucleotide sequences or small domains and motifs in protein sequences.

PepCyber:P~PEP -- a database of human protein protein interactions mediated by phosphoprotein-binding domains

Database specialized in documenting human PPBD-containing proteins and PPBD-mediated interactions.

PeptideCutter -- protein cleavage sites prediction tool

Predicts potential protease cleavage sites and sites cleaved by chemicals in a given protein sequence.

Phobius -- A combined transmembrane topology and signal peptide predictor

Predict combined transmembrane topology and signal peptides.

Phospho.ELM -- a database of phosphorylation sites

Search for eukaryotic phosphorylation sites.

Phospho3D -- a database of three-dimensional structures of protein phosphorylation sites

Search for 3D structure and functional annotation of phosphorylation sites in proteins.

PhosphoSite -- A bioinformatics resource dedicated to physiological protein phosphorylation.

Search the database of in vivo phosphorylation sites of human and mouse proteins

PolyQ -- Polyglutamine Database

Find information about polyglutamine (polyQ) repeats.

Pratt Protein motif and pattern discovery

Find the presence of protein motifs and patterns in an amino acid sequence.

PrediSi -- Prediction of Signal Peptides and their Cleavage Positions

Predict signal peptide sequences and their cleavage positions in bacterial and eukaryotic amino acid sequences.

ProFunc -- a server for predicting protein function from 3D structure

Predict protein functions based on known structures.

ProMateus--an open research approach to protein-binding sites analysis

Predict the location of potential protein-protein binding sites for unbound proteins.

ProTeus -- identifying signatures in protein termini

Identify short linear signatures in protein termini.

ProtSweep -- protein annotation by homology

Analyze and identify newly obtained protein sequences.

Protemot -- prediction of protein binding sites with automatically extracted geometrical templates

Predict protein binding sites in a protein sequence based on geometrical analysis of protein tertiary substructures.

QuasiMotiFinder -- protein annotation by searching for evolutionarily conserved motif-like patterns

Search for evolutionarily conserved motif-like patterns in protein sequences.

RNABindR -- software for prediction of RNA binding residues in proteins

Web-based server for analyzing and predicting RNA binding sites in proteins.

SCANMOT -- searching for similar sequences using a simultaneous scan of multiple sequence motifs

Search for similarities between proteins by simultaneous matching of multiple motifs.

SDPpred -- A Tool for Prediction of Amino Acid Residues that Determine Differences in Functional Specificity of Homologous Proteins

Predict residues in protein sequences that determine the proteins' functional specificity.

SDR -- Specificity Determining Residues Database

Predict specificity-determining residues in protein families.

SLiMDisc -- Short, Linear Motif Discovery

Find shared motifs in proteins with a common attribute.

SUMOsp -- a web server for sumoylation site prediction

Conduct in silico sumoylation sites prediction.

SWAKK -- a web server for detecting positive selection in proteins using a sliding window substitution rate analysis

Detect protein sequence section under positive evolution selection.

ScanProsite

Search for motifs and patterns within protein sequences.

ScanProsite -- detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins

Detect patterns, profiles and motifs in a protein sequence.

ScanSite 2.0 -- Proteome-wide prediction of cell signaling interactions using short sequence motifs

Search for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains.

SePreSA -- SErver for the PREdiction of populations susceptible to Serious Adverse drug reaction

Find information about populations carrying polymorphisms within protein binding pockets that make them susceptible to serious adverse drug reaction (SADR).

Sequence Motif Search

Search the presence of a motif in either amino acid sequence or nucleotide sequence.

Signal-3L -- A 3-layer approach for predicting signal peptides

Predict signal peptides.

SignalP -- Machine learning approaches to the prediction of signal peptides, their cleavage sites, and other protein sorting signals

Predict signal peptides and their cleavage sites.

Sulfinator -- tyrosine sulfation sites prediction tool

Predict the presence of tyrosine sulfation sites in protein sequences

SuperSite -- Ligand Binding Site Database

Look at protein structure from a ligand and binding site perspective.

Swiss EMBnet node web server

Use a collection of bioinformatics tools at this portal site.

T-REKS -- identification of Tandem REpeats in sequences with a K-meanS based algorithm

Find information about tandem repeats in proteins that carry fundamental biological functions and are related to a number of human diseases.

TMFunction -- The Functional Database of Membrane Proteins

Find information about functional residues in alpha-helical and beta-barrel membrane proteins.

TOPDOM -- Conservatively Located Domains and Motifs in Transmembrane Proteins

Database of domains and motifs with conservative location in transmembrane proteins.

The EMOTIF database

Search for highly conserved and specific protein sequence motifs.

TreeDet -- Predicting Functional Residues in Protein Sequence Alignments

Predict functional sites in protein sequence alignments use different methodologies.

W-ChIPMotifs -- ChIP-based protein Motif discovery web server

Find de novo protein motifs from chromatin immunoprecipitation data.

WebFEATURE -- an interactive web tool for identifying and visualizing functional sites on macromolecular structures

Scan query structures for functional sites in both proteins and nucleic acids.

WebProAnalyst -- an interactive tool for analysis of quantitative structurex96activity relationships in protein families

Analyze quantitative structure-activity relationship of related protein families.

eBLOCKs -- enumerating conserved protein blocks to achieve maximal sensitivity and specificity

Search for ungapped alignments of highly conserved regions among a protein family or superfamily.

eF-seek -- prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape

Predict the functional sites of proteins.

firestar -- prediction of functionally important residues using structural templates and alignment reliability

An expert system for predicting ligand-binding residues in protein structures.

iMOTdb -- a comprehensive collection of spatially interacting motifs in proteins

Automatically identify spatially interacting motifs among distantly related proteins sharing similar folds and possessing common ancestral lineage.

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.

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.