BOL: Related items

What is Health Informatics?

Wed, 12 Mar 2014 14:50:46 -0500

What is health informatics? In the words of Dr. Noni MacDonald...: "Most of the way I've seen it defined is the intersection with health information, computer science and health care and health systems but I think that's very linear and very narrow in what it is. For me what Health Informatics is really is about is how do we take all of these tools and have everybody able to manage health, health care systems and their own personal health in a better way. That's whether you're the mayor of the city, whether you're the Dean of Medicine, whether you're the CEO of one of the biggest health organization or you're John Q Public who's just cut their finger. That's what it's all about." Filmed at Dalhousie University during summer 2010. Edited by Mohammed Al-Bakri during summer 2011. Thanks to the participants: Dr. Grace Paterson Dr. Noni MacDonald Dr. Ray LeBlanc Dr. Ajantha Jayabarathan Mr. Amir Feridooni Dr. Raza Abidi Dr. Brett Taylor

India and Germany to begin joint research in the area of 'Bioinformatics in Health Research'

Rahul Nayak — Wed, 17 Jan 2018 14:10:36 -0600

To facilitate bilateral cooperation in biotechnology between the scientific communities of India and Germany, the Department of Biotechnology (DBT) will soon begin collaborative research in the identified priority area of 'Bioinformatics in Health Research' under the programme of Indo-German Cooperation in Health Research.

The purpose of the programme is to stimulate new collaborations, e.g. the preparation of joint projects under national funding programmes. The programme facilitates bilateral cooperation in biotechnology between the scientific communities of India and Germany by way of joint research projects which will encompass bilateral workshops/seminar and exchange visits of scientists.

The programme is being implemented within the agreement of Indo-German cooperation in S&T of 1974, under which the Department of Biotechnology, Government of India and Forschungszentrum Julich BMBH (FZJ), Federal Republic of Germany, have agreed for cooperative programme in biotechnology.

DBT of the Ministry of Science & Technology, Government of India and the Project Management Agency at the German Aerospace Center (DLR-PT, European and International Cooperation), Bonn are the nodal implementing agencies from the Indian and German side respectively.

Through this programme, it is expected that the funded cooperation enables the partners to develop applicable scientific results which can be published and/ or could be commercialised and may lead to formation of joint ventures. All publications, patents coming out of these projects, need to be jointly authored by both Indian and German scientists. All necessary approvals like ethical clearance, HMSC approval from Indian point of view as well as EU, if applicable, from German point of view, e.g. before conducting animal experimentation if any needs to be obtained by PIs before undertaking the project.

Now, both the nodal agencies have invited research proposals in identified priority area of 'Bioinformatics in Health Research' from eligible scientists. Joint research projects are required to be submitted to both the nodal agencies by 15 January 2018. Scientists/faculty members working in regular capacity in universities, national R&D laboratories/institutes and private R&D institutes can be part of this joint research programme. For the private sector, partners from all kind of private sectors are eligible, but financing is limited. For Indian scientists from the private sector, only local hospitality in Germany as part of the exchange visit is available from the German side. For German scientists from the private sector, only travel costs are available for small and medium size enterprises (for definition of SME ref. to 2003/361/EC) as well as local hospitality in India will be borne by themselves.

MPXV Bookmarks

BioStar — Mon, 19 Dec 2022 01:58:20 -0600

MPVX infection across the globe

https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html

Address of the bookmark: https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html

Abe lab／International Research Center for Infectious Diseases Laboratory of Bacterial Pathogenesis

Fri, 11 Sep 2026 13:57:33 -0500

Worldwide rapid dissemination of antimicrobial resistance (AMR) is staggering, and the number of deaths associated with AMR is estimated to exceed that of deaths due to cancers in the near future unless the global response is mounted. There is no doubt that antimicrobial use itself is a direct cause of antimicrobial resistance, but it is still challenging to diagnose bacterial infections and use antimicrobials appropriately in current clinical settings. Our goal is to contribute to better diagnostics and treatment guidelines by revealing the interrelationships among pathogens, host immunity, and antimicrobial agents.

More at https://www.biken.osaka-u.ac.jp/en/laboratories/detail/68

Genome Browsers

Rahul Agarwal — Fri, 16 Aug 2013 19:04:47 -0500

Genome Browser is the platform/database used for searching and retreiving sequences and annotation of genomes belong to various eukaryotes, prokaryotes, etc.

Following are the weblink for different available browsers:

http://www.ensembl.org/index.html

http://ensemblgenomes.org/

http://genome.ucsc.edu/

http://www.ncbi.nlm.nih.gov/genome

http://www.ebi.ac.uk/genomes/

http://flybase.org/

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

http://www.sanger.ac.uk/resources/databases/

Bacterial genome assembly !!

Jit — Fri, 05 May 2017 06:11:22 -0500

This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of bacterial sequence data. The bacterial sample used in this tutorial will be referred to simply as “Species” since it is live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.

https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md

Address of the bookmark: http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/

KOALA: KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation

Abhimanyu Singh — Wed, 12 Dec 2018 09:16:55 -0600

KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. BlastKOALA and GhostKOALA assign K numbers to the user's sequence data by BLAST and GHOSTX searches, respectively, against a nonredundant set of KEGG GENES. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to the BlastKOALA server and can be executed in an interactive mode. See Step-by-step Instructions.

Reference: Kanehisa, M., Sato, Y., and Morishima, K. (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726-731. [pubmed] [pdf]

Address of the bookmark: https://www.kegg.jp/blastkoala/

Exploring Bacterial Comparative Genomics: A Bioinformatics Approach

LEGE — Sat, 14 Dec 2024 12:31:14 -0600

In the world of microbiology, bacteria have long fascinated scientists for their diversity, adaptability, and crucial roles in ecosystems and human health. Comparative genomics—a field that involves analyzing and comparing the genomes of different organisms—has revolutionized our understanding of bacterial evolution, adaptation, and pathogenicity. By leveraging bioinformatics tools and techniques, researchers can uncover genomic insights that were once hidden. This blog delves into the principles, methodologies, and applications of bacterial comparative genomics from a bioinformatics perspective.

What is Bacterial Comparative Genomics?

Comparative genomics involves the systematic comparison of genomes across different bacterial species or strains. This approach allows scientists to:

Identify conserved and unique genes.
Explore genetic determinants of pathogenicity.
Understand bacterial evolution and phylogenetics.
Investigate horizontal gene transfer and its role in antibiotic resistance.

Bioinformatics is central to these analyses, enabling the processing and interpretation of large-scale genomic data.

Key Steps in Bacterial Comparative Genomics

Genome Sequencing and Assembly: The process begins with obtaining high-quality bacterial genome sequences. Advances in next-generation sequencing (NGS) technologies have made it faster and more affordable to sequence bacterial genomes. Tools such as SPAdes and Velvet are commonly used for genome assembly.
Genome Annotation: Annotating a genome involves identifying genes, regulatory elements, and other genomic features. Automated tools like Prokka and RAST provide functional annotations, allowing researchers to predict the roles of genes and proteins.
Genome Alignment: Aligning genomes is crucial for identifying conserved regions, single-nucleotide polymorphisms (SNPs), and structural variations. Tools like Mauve and progressiveMauve are commonly employed for whole-genome alignments.
Comparative Analyses:
- Core and Pan-genome Analysis: The core genome consists of genes shared across all strains of a species, while the pan-genome includes all genes found in any strain. Software like Roary and BPGA can perform core and pan-genome analyses.
- Phylogenetic Analysis: Comparative genomics often involves reconstructing evolutionary relationships. Tools such as MEGA and IQ-TREE facilitate phylogenetic tree construction based on genomic data.
- Functional Enrichment Analysis: To understand the biological significance of unique or shared genes, functional enrichment analysis using databases like GO (Gene Ontology) and KEGG is essential.

Recommended Bioinformatics Tools for Comparative Genomics

Here are some additional bioinformatics tools that can aid bacterial comparative genomics:

OrthoFinder: For accurate ortholog identification across multiple genomes.
PanOCT: Specifically designed for pan-genome clustering and annotation.
FASTANI: A tool for calculating Average Nucleotide Identity (ANI) for microbial genome comparisons.
CIRCOS: For visually comparing genomic data through circular genome plots.
Galaxy Platform: A user-friendly web-based platform offering numerous genomic analysis tools.
BLAST: Essential for sequence alignment and similarity searches.
PhyloSift: Focused on phylogenetic analysis of microbial genomes using marker genes.

These tools, in combination with the methods discussed, provide a robust framework for conducting comprehensive comparative genomic studies.

Applications of Bacterial Comparative Genomics

Understanding Pathogenicity: Comparative genomics helps identify virulence factors that distinguish pathogenic strains from non-pathogenic relatives. For instance, comparing genomes of Escherichia coli strains has revealed key genetic determinants of pathogenicity in enterohemorrhagic strains.
Antibiotic Resistance Research: The spread of antibiotic resistance genes through horizontal gene transfer is a major global concern. Comparative analyses can trace the origins and dissemination of resistance genes, aiding in the development of countermeasures.
Microbial Ecology and Evolution: By studying genomic variations, researchers can understand how bacteria adapt to different environments. This is particularly relevant for extremophiles and symbiotic bacteria.
Vaccine Development: Identifying conserved antigens across pathogenic strains is critical for vaccine design. Comparative genomics has been instrumental in developing vaccines against pathogens like Neisseria meningitidis.
Biotechnology Applications: Comparative studies can uncover unique metabolic pathways in bacteria, paving the way for applications in bioremediation, synthetic biology, and industrial microbiology.

Challenges in Bacterial Comparative Genomics

While the field has made significant strides, several challenges remain:

Data Overload: The rapid growth of sequencing data requires robust computational infrastructure and efficient algorithms.
Genome Plasticity: High rates of horizontal gene transfer and genome rearrangements in bacteria complicate comparative analyses.
Annotation Accuracy: Automated annotation tools are not infallible, and manual curation is often needed for high-confidence results.
Interpreting Non-Coding Regions: Understanding the functional significance of non-coding genomic regions remains a challenge.

Future Directions

The integration of bacterial comparative genomics with other ‘omics’ approaches—such as transcriptomics, proteomics, and metabolomics—promises a more comprehensive understanding of bacterial biology. Additionally, advancements in machine learning and artificial intelligence are likely to further enhance bioinformatics analyses, enabling the prediction of complex phenotypes from genomic data.

Conclusion

Bacterial comparative genomics, driven by bioinformatics, continues to unravel the complexities of bacterial life. From combating antibiotic resistance to uncovering the secrets of microbial evolution, this interdisciplinary field holds immense potential for addressing pressing challenges in microbiology and beyond. As technology advances, so too will our ability to harness the power of comparative genomics for scientific and societal benefit.

GIPSy2 Detect Hidden Islands Inside Bacteria

BioStar — Mon, 24 Aug 2026 18:15:58 -0500

Imagine a tiny bacterium living in a crowded environment.

It looks simple, but inside its microscopic body is a huge library of DNA. Most of this DNA has been passed down from its parents. But sometimes, bacteria can pick up new pieces of DNA from other bacteria.

These new pieces can give them useful abilities — such as surviving antibiotics, causing disease, or adapting to a new environment.

Scientists call some of these special DNA regions genomic islands.

But there is a problem: How do we find these hidden islands?

That is where GIPSy2 comes in.

Researchers developed GIPSy2, a computer tool that acts like a detective. It scans bacterial DNA and looks for unusual patterns that might show where a genomic island is hiding.

Instead of looking at just one clue, GIPSy2 uses several methods to investigate the DNA. It can also study many bacterial genomes, making it useful when researchers have large amounts of genetic data.

In their study, the researchers tested GIPSy2 on different bacteria. The tool was able to identify genomic regions connected with important features such as antibiotic resistance, disease-causing abilities, metabolism, and relationships with other organisms.

Think of it like searching for hidden islands on a huge map. The DNA is the ocean, and genomic islands are the small pieces of land that may contain valuable information.

GIPSy2 does not give scientists the final answer by itself. Its predictions still need to be carefully checked and, when possible, confirmed through experiments.

But it gives researchers a faster way to explore bacterial genomes and discover clues about how bacteria change and survive.

And that is why this small piece of software could help scientists better understand the invisible world of bacteria — one hidden genomic island at a time.

GIPSy2 is currently available on Zenodo repository at https://zenodo.org/doi/10.5281/zenodo.10222587

Gupta Lab

Sat, 29 Dec 2018 13:18:31 -0600

Work include (i) understanding the evolutionary relationships among different prokaryotic and eukaryotic organisms; (ii) Understanding the cellular functions of these lineage-specific signature proteins as well as lineage-specific conserved inserts and deletions in important housekeeping proteins by genetic and biochemical studies; (iii) Development of novel diagnostic methods (PCR based and immunological) for identification of different groups of organisms based upon these signature proteins and conserved indels; (iv) The use of these lineage-specific probes with predicitive ability to identify/explore the presence of different groups of organisms in metagenomic sequences from various environments.

https://fhs.mcmaster.ca/gupta-lab/index.html