BOL: Related items

BioGPS: Spotlight on the Gene Expression Atlas

Jit — Thu, 18 Oct 2018 12:15:12 -0500

BioGPS opened 2016 with a publication in Nucleic Acids Research, right after the New Year holiday. Throughout the year, new designs for the site were being created, reviewed, adjusted, reviewed, adjusted, and more review/adjustments in anticipation of a site redesign for 2017. A Plugin registration Blitz was held in March and April; followed by a Plugin Review Blitz in May. The BioGPS spotlight series was also restarted, with spotlights on BGEE, Intermine, and other Intermine-related plugins.

There were ~910,000 requests made to BioGPS in 2016. Requests to BioGPS peaked in March and at the lowest in December.

Address of the bookmark: http://biogps.org/

WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results

BioStar — Sun, 12 Apr 2020 10:02:22 -0500

WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we’ve made:
1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.
2. We have added the reference data of 9 species for users selection.
3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.

Address of the bookmark: http://wego.genomics.org.cn/

KOBAS: a web server for gene/protein functional annotation and functional gene set enrichment

Jit — Fri, 19 Oct 2018 09:36:11 -0500

KOBAS 3.0 is a web server for gene/protein functional annotation (Annotate module) and functional gene set enrichment(Enrichment module). For Annotate module, it accepts gene list as input, including IDs or sequences, and generates annotations for each gene based on multiple databases about pathways, diseases, and Gene Ontology. For Enrichment module, it can accept either gene list or gene expression data as input, and generates enriched gene sets, corresponding name, p-value or a probability of enrichment and enrichment score based on results of multiple methods.

Address of the bookmark: http://kobas.cbi.pku.edu.cn/

Mercator: Multiple Whole-Genome Orthology Map Construction

Jit — Tue, 19 May 2020 16:46:22 -0500

Whole-genome homology maps attempt to identify the evolutionary relationships between and within multiple genomes. The term "syntenic" is often used to describe regions of multiple genomes that are believed to have evolved from the same region in an ancestral genome. However, it has been pointed out that this use of the term is incorrect (Passarge et al. 1999) and thus we will use the terms "homologous", "orthologous", and "paralogous" instead. Ideally, given K genomes, we would like to identify all orthologous genomic regions as well as paralogous regions within each genome and hypothetical ancestral genome. Maps listing these relationships are extremely valuable to researchers performing comparative analyses of genomic sequence. Here we present our initial work in the form a program called Mercator that constructs orthology maps between multiple whole genomes.

Address of the bookmark: https://www.biostat.wisc.edu/~cdewey/mercator/

AlfaPang: alignment free algorithm for pangenome graph construction

BioStar — Thu, 28 Aug 2025 02:56:35 -0500

AlfaPang constructs variation graphs, leveraging its alignment-free and reference-free approach, based solely on intrinsic sequence properties. This design allows AlfaPang's runtime and memory usage to scale linearly with the size of input sequences, enabling it to handle significantly larger genome sets compared to other methods.

Address of the bookmark: https://github.com/AdamCicherski/AlfaPang

RNA-Seq differential expression work flow using DESeq2

BioStar — Mon, 23 Aug 2021 10:57:14 -0500

One of the aim of RNAseq data analysis is the detection of differentially expressed genes. The package DESeq2 provides methods to test for differential expression analysis.

Address of the bookmark: http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2

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

Research Associate (RA) at IOB

Mon, 05 May 2014 08:38:54 -0500

Applications are invited for a post of Research Associate (RA) or Senior Research Fellow (SRF) in the ICMR project on "Integrated Analysis of Multi-omics Data in Human Gliomas".

We are looking for a motivated candidate for handling proteomic and/or transcriptomic and other data with a strong background in bioinformatics tools and database development. The project will include identification of novel peptides from mass spectrometry-based proteomic data.

Familiarity with statistical tools or wet lab experience will be an added advantage. The position is open for immediate appointment and available for two years. The applicant will be appointed as Research Associate or Senior Research Fellow based on qualifications as detailed below:

Research Associate: Ph.D. in Biological Science or Bioinformatics with relevant publications in peer reviewed journals. Familiarity with bioinformatics tools, database development, programming skills and proteomic and/or other omics data analysis. Salary will be as per ICMR rules and guidelines.

Senior Research Fellow: M.Sc./B.Tech. in any branch of biology/ biotechnology/bioinformatics, with minimum 2 years of research experience (essential). Familiarity with bioinformatics tools, database development, programming skills and proteomic data analysis. Salary will be as per ICMR rules and guidelines.

Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.

Interested candidates may send a Letter of Interest and CV by email to: ravi@ibioinformatics.org on or before May 15th, 2014.

Contact:
Dr. Ravi Sirdeshmukh
Distinguished Scientist & Associate Director, IOB,
Principal Advisor MSMC/MSCTR

Advertisement: www.ibioinformatics.org/careers.php

Assistant Professor (Bio-Informatics) at Health and Family Welfare Department (Medical Education) in Raipur

Wed, 07 May 2014 00:08:38 -0500

Advertisement No.05/2014/ Exam/Dated 17/04/2014

No of vacancies: 01

Pay scale:Rs. 15600 – 39100 + 6600/-

Essential Academic Qualifications / Experience : Good academic record as defined by the concerned university with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master's Degree level in a relevant subject from an Indian University, or an equivalent degree from an accredited foreign university.

Besides fulfilling the above qualifications, the candidate must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/ SET.

Notwithstanding anything contained in sub-clauses (a) and (b) to this Clause, candidates, who are, or have been awarded a Ph.D. Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations, 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor or equivalent positions in Universities/Colleges/Institutions.

NET/SLET/SET shall also not be required for such Masters Programmes in disciplines for which NET/SLET/SET is not conducted.

Apply online: http://www.psc.cg.gov.in/htm/OA_ME2014.html

Last Date for Online Registration: 22/05/2014

For more details: http://www.psc.cg.gov.in/pdf/Advertisement/ADV_ME2014.pdf

Sequence Viewer: Download Transcripts, Exons and Proteins

Mon, 15 Sep 2014 17:30:36 -0500

How to download FASTA sequence for certain gene features while in the NCBI's Sequence Viewer. Sequence Viewer homepage: www.ncbi.nlm.nih.gov/projects/sviewer/ Sequence Viewer playlist: https://www.youtube.com/playlist?list=PL76D7EE6A6A8AC1C3