BOL: Related items

gggenomes: A grammar of graphics for comparative genomics

Surabhi Chaudhary — Mon, 01 Feb 2021 14:47:32 -0600

gggenomes is a versatile graphics package for comparative genomics. It extends the popular R visualization packageggplot2 by adding dedicated plot functions for genes, syntenic regions, etc. and verbs to manipulate the plot to, for example, quickly zoom in into gene neighborhoods.

Address of the bookmark: https://github.com/thackl/gggenomes

Pevzner Lab !

Thu, 02 Nov 2023 05:39:26 -0500

The laboratory works on genome sequencing, immunoproteogenomics, antibiotics sequencing, and comparative genomics - computational technologies that enabled new applications and allowed scientists to attack biological problems that remained beyond the reach of previous techniques.

https://bioalgorithms.ucsd.edu/research4.html

Phylogenetic for Bioinformatics

Jitendra Narayan — Tue, 16 Jul 2013 03:50:30 -0500

Biologists estimate that there are about 5 to 100 million species of organisms living on Earth today. Evidence from morphological, biochemical, and gene sequence data suggests that all organisms on Earth are genetically related, and the genealogical relationships of living things can be represented by a vast evolutionary tree, the Tree of Life. The Tree of Life then represents the phylogeny of organisms, i. e., the history of organismal lineages as they change through time.
Every living organism contains DNA, RNA, and proteins. Closely related organisms generally have a high degree of agreement in the molecular structure of these substances, while the molecules of organisms distantly related usually show a pattern of dissimilarity. Molecular phylogeny uses such data to build a "relationship tree" that shows the probable evolution of various organisms. Not until recent decades, however, has it been possible to isolate and identify these molecular structures.
phylogenetics is the study of evolutionary relatedness among various groups of organisms (for example, species or populations), which is discovered through molecular sequencing data and morphological data matrices. In other word, Phylogenetics, the science of phylogeny, is one part of the larger field of systematics, which also includes taxonomy. Taxonomy is the science of naming and classifying the diversity of organisms Molecular phylogeny is the use of the structure of molecules to gain information on an organism's evolutionary relationships. The result of a molecular phylogenetic analysis is expressed in a so-called phylogenetic tree.

The evolutionary connections between organisms are represented graphically through phylogenetic trees. Due to the fact that evolution takes place over long periods of time that cannot be observed directly, biologists must reconstruct phylogenies by inferring the evolutionary relationships among present-day organisms.
Application of the techniques that make this possible can be seen in the very limited field of human genetics, such as the ever more popular use of genetic testing to determine a child's paternity, as well as the emergence of a new branch of criminal forensics focused on genetic evidence.
The effect on traditional scientific classification schemes in the biological sciences has been dramatic as well. Work that was once immensely labor- and materials-intensive can now be done quickly and easily, leading to yet another source of information becoming available for systematic and taxonomic appraisal. This particular kind of data has become so popular that taxonomical schemes based solely on molecular data may be encountered. Proponents even claim that taxonomy was previously based on morphology alone, which of course is utter fable.

For additional information on phylogenetics, see list of Phylogenetics Resources on the Internet.

Phylogeny and Reconstructing Phylogenetic Trees: http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html
the CBRG and Department of Statistics Phylogeny tutorial: http://www.compbio.ox.ac.uk/tutorials/phylogeny/
TUTORIAL: PHYLOGENETIC ANALYSIS USING PARSIMONY:http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html

PHYLIP: http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html
An Introduction to Molecular Phylogeny: http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf

How to make a phylogenetic tree: http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Treetutorial.html
Phylogenetic Trees: http://cnx.org/content/m11052/latest/
Phylogeny by Ron Shamir: http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf
Introduction to Phylogeny: http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm
Lecturer notes on Phylogeny: http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf
Principles and Practice of Phylogenetic Systematics:http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm

Inferring phylogenetic trees: http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf

Lecture Notes

Chapter 1 - The Diversity, Classification, and Evolution of Vertebrates:http://academic.emporia.edu/mooredwi/nathist/chap1.htm

Algorithms for Phylogenetic Reconstructions:http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf

Phylogeny.fr is a free, simple to use web service dedicated to reconstructing and analysing phylogenetic relationships between molecular sequences. Phylogeny.fr runs and connects various bioinformatics programs to reconstruct a robust phylogenetic tree from a set of sequences. For more detail : http://www.phylogeny.fr/version2_cgi/index.cgi

A Brief Tutorial on Phylogenetics
http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf

A Brief Tutorial on Phylogenetics Human Rabbit Chicken
http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf

Phylogenetic Tree Computation Tutorial Overview
http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf

MrBayes: A program for the Bayesian inference of phylogeny
http://golab.unl.edu/teaching/SBseminar/manual.pdf

Web sites providing software for the construction of phylogenetic trees

BioEdit

Coelocanth-Fish Out of Time

Computational Biochemistry Research Group

Digital Taxonomy

Hennig 86

Hyperclean from Bioinformatics Solutions, Inc.

Memorial University of Newfoundland

Mr. Bayes

NONA

Oxford University Evolutionary Biology Group

Paleobiology Database

PAUP

Phylip Homepage

Sinauer Associates

TNT-Tree Analysis Using New Technology

Tree Base

Treefinder

Tree-Puzzle

Tree View-Taxonomy and Systematics Group at Glasgow

Washington University-List of Phylogeny Software

CAMSA :: a tool for Comparative Analysis and Merging of Scaffold Assemblies

Rahul Nayak — Thu, 28 Dec 2017 09:10:26 -0600

CAMSA – is a tool for Comparative Analysis and Merging of Scaffold Assemblies, distributed both as a standalone software package and as Python library under the MIT license.

Main features:

works with any number of scaffold assemblies in de-novo non-progressive fashion
allows to simultaneously work with scaffold assemblies obtained from any in silico and in vitro techniques, supporting multiple existing formats via built-in converters
creates an extensive report with several comparative quality metrics (both on assembly level and on the level of individual assembly points)
constructs a merged combined scaffold assembly
provides an interactive framework for a visual comparative analysis of the given assemblies

Address of the bookmark: https://cblab.org/camsa/

MGcV: the microbial genomic context viewer for comparative genome analysis

Jit — Mon, 29 Jan 2018 04:55:46 -0600

MGcV is an interactive web-based visalization tool tailored to facilitate small scale genome analysis. To start using MGcV:

Supply your genes/genomic segments/phylogenetic tree of interest in the input-box by
- selecting the type of identifier and pasting identifiers (one per line)
- or by using the gene ID search tool
- or with the BLAST search tool
Click "Visualize context".

Consult the documentation to learn more about MGcV.

Address of the bookmark: http://mgcv.cmbi.ru.nl/

geck: trio-based comparative benchmarking of variant calls

Jit — Sun, 19 May 2019 20:54:12 -0500

Determine the accuracy of our model by comparing the precision and recall of GATK Unified Genotyper and Haplotype Caller on the high-confidence SNPs of the NIST Ashkenazim trio and the two independent Platinum Genome trios. We show that our method is able to estimate differential precision and recall between the two pipelines with 10−3uncertainty.

Address of the bookmark: https://github.com/sbg/geck

The Centre for Bioinformatics (MCB) Lab

Sun, 14 Jul 2013 12:41:20 -0500

The Centre for Bioinformatics (MCB) is a diverse collection of professors, postdoctoral fellows, and students, who share a common interest in Bioinformatics.

Research Area

We are interested in the development of the statistics and computational methods for the analysis of this data in breast cancer.
We have worked on probabilistic models for subcellular localization, protein-protein interactions, and problems related to chemical genomics.
We are interested in the development of bioinformatics/biostatistical methodology in the analysis of epigenetic/epigenomic data.
We are interested in integrative bioinformatics approaches to learn the gene, gene products, interactions, and regulatory mechanisms involved in mental retardation.

Link @ http://www.mcgill.ca/mcb/

Jayaram Lab

Sun, 14 Jul 2013 14:04:37 -0500

Responsible (a) for developing Chemgenome, Bhageerath & Sanjeevini methods & softwares for genome annotation, protein tertiary structure prediction & computer aided drug design respectively, (b) for setting up a multi-teraflop supercomputing facility for Bioinformatics & Computational Biology at IIT Delhi, and (c) for making the hardware and software freely accessible at (www.scfbio-iitd.res.in) to the global scientific user community.

Faculty facilitator/Founder Director for two start-up companies (Leadinvent incubated at IIT, Delhi from 2006-2009 & Novoinformatics, under incubation at IIT Delhi since 2011).

Research Interest
Genome Analysis, Protein Structure Prediction and Drug Design.

Link @ http://www.scfbio-iitd.res.in/

Genomics for Bioinformatician

Jitendra Narayan — Sat, 20 Jul 2013 07:03:00 -0500

Genomics is the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping efforts. The field also includes studies of intragenomic phenomena such as heterosis, epistasis, pleiotropy and other interactions between loci and alleles within the genome. In contrast, the investigation of the roles and functions of single genes is a primary focus of molecular biology or genetics and is a common topic of modern medical and biological research. Research of single genes does not fall into the definition of genomics unless the aim of this genetic, pathway, and functional information analysis is to elucidate its effect on, place in, and response to the entire genome's networks.

Genomics was established by Fred Sanger when he first sequenced the complete genomes of a virus and a mitochondrion. His group established techniques of sequencing, genome mapping, data storage, and bioinformatic analyses in the 1970-1980s. A major branch of genomics is still concerned with sequencing the genomes of various organisms, but the knowledge of full genomes has created the possibility for the field of functional genomics, mainly concerned with patterns of gene expression during various conditions. The most important tools here are microarrays and bioinformatics. Study of the full set of proteins in a cell type or tissue, and the changes during various conditions, is called proteomics. A related concept is materiomics, which is defined as the study of the material properties of biological materials (e.g. hierarchical protein structures and materials, mineralized biological tissues, etc.) and their effect on the macroscopic function and failure in their biological context, linking processes, structure and properties at multiple scales through a materials science approach. The actual term 'genomics' is thought to have been coined by Dr. Tom Roderick, a geneticist at the Jackson Laboratory (Bar Harbor, ME) over beer at a meeting held in Maryland on the mapping of the human genome in 1986.

The outcome of almost two years of intense discussions with literally hundreds of scientists and members of the public, has three major areas of focus: Genomics to Biology, Genomics to Health, and Genomics to Society.

Genomics to Biology:
The human genome sequence provides foundational information that now will allow development of a comprehensive catalog of all of the genome's components, determination of the function of all human genes, and deciphering of how genes and proteins work together in pathways and networks.

Genomics to Health:
Completion of the human genome sequence offers a unique opportunity to understand the role of genetic factors in health and disease, and to apply that understanding rapidly to prevention, diagnosis, and treatment. This opportunity will be realized through such genomics-based approaches as identification of genes and pathways and determining how they interact with environmental factors in health and disease, more precise prediction of disease susceptibility and drug response, early detection of illness, and development of entirely new therapeutic approaches.

Genomics to Society:
Just as the HGP has spawned new areas of research in basic biology and in health, it has created new opportunities in exploring the ethical, legal, and social implications (ELSI) of such work. These include defining policy options regarding the use of genomic information in both medical and non-medical settings and analysis of the impact of genomics on such concepts as race, ethnicity, kinship, individual and group identity, health, disease, and "normality" for traits and behaviors.

This vision for the future of genomics is not just about the NHGRI. It encompasses the whole field of genomics, including the work of all the other Institutes and Centers at the NIH and of a number of other federal agencies. All of the NIH Institutes are already taking full advantage of the sequence and will apply its data to the better understanding of both rare and common diseases, almost all of which have a genetic component. A recent example of the way that the HGP and the knowledge and new technologies it has spawned are already facilitating science is the extremely rapid sequencing by groups in Canada and at the Centers for Disease Control and Prevention (CDC) in Atlanta of the genome of the virus that causes Severe Acute Respiratory Syndrome (SARS). The sequencing of the SARS virus genome provides insight into this new and deadly disease at a speed never before possible in science. In turn, this should lead to the rapid development of diagnostic tests and, in time, vaccines and effective treatments.

Links for the addition material available on Net

Genomes and genomics:

Bioinformatics and Genomics:

Structural genomics tutorial:

Comparative Genomics Tutorial:

GENOME TUTORIAL:

Tools and resources for identifying protein families, domains and motifs

Bioinformatics Tools
Tips, Tutorials, and Terminology for Using Selected Resources in Genome Database Guide:

A Web-Based Comparative Genomics Tutorial for Investigating Microbial Genomes:

Free Online Tutorials Teach Anyone How to Use Genome Databases:

Circos to create concise, explanatory, unique and print-ready visualizations of your data:

Genomics and Comparative Genomics Learning Module:

Computational Challenges in Comparative Genomics

A Tutorial:

A Comparative Genomics Resource for Grains:

PLAZA: A Comparative Genomics Resource to Study Gene and Genome Evolution in Plants:

VISTA :

Software for Genomics

Artemis Artemis is a free genome viewer and annotation tool that allows visualization of sequence features and the results of analyses within the context of the sequence, and its six-frame translation.
Chromas It will display and prints chromatogram files from ABI automated DNA sequencers, and Staden SCF files which the analysis programs for ALF, Li-Cor and Visible Genetics OpenGene sequencers can create.
Glimmer A system for finding genes in microbial DNA, especially the genomes of bacteria and archaea.Glimmer (Gene Locator and Interpolated Markov Modeler) uses interpolated Markov models (IMMs) to identify the coding regions and distinguish them from noncoding DN
Glimmer HMM A fast and accurate gene finder based on a GHMM architecture, developed specifically for eukaryotes. It incorporates splice site models adapted from the GeneSplicer program and uses interpolated Markov models for evaluating the coding regions.
Glimmer M A gene finder derived from Glimmer, but developed specifically for eukaryotes. It is based on a dynamic programming algorithm that considers all combinations of possible exons for inclusion in a gene model and chooses the best of these combinations. The d
MUMmer MUMmer is a system for rapidly aligning entire genomes, whether in complete or draft form.
pDRAW pDRAW32 is being developed as a free time hobby project. It is far from finished, but as it has reached a point where it could be helpful for many labs, it is now available to the scientific community.
Sequin Sequin is a stand-alone software tool developed by the NCBI for submitting and updating entries to the GenBank, EMBL, or DDBJ sequence databases. It is capable of handling simple submissions that contain a single short mRNA sequence, and complex submissio
Staden The Staden Package consists of a series of tools for DNA sequence preparation (pregap4), assembly (gap4), editing (gap4) and DNA/protein sequence analysis (spin).

For more software @ http://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools

Personalised Medicine - Animation

Tue, 27 Aug 2013 10:07:24 -0500

Two animated case scenarios set now and in the future. These highlight potential differences in the way patients are treated now, and how they might be treated as healthcare becomes more tailored.