BOL: Related items

AI Uncovers Hidden Secrets in Bacterial DNA, Opening New Frontiers in Genomic Research

Jitendra Narayan — Fri, 25 Sep 2026 22:38:42 -0500

Scientists are now using artificial intelligence in order to examine sections of bacterial DNA that have not been looked at before. This method is showing potential RNA interactions and previously unknown genetic systems which could alter our understanding of microbes. A new study presents Minerva, a genome language model, demonstrating that AI can assist researchers in identifying biological patterns that traditional techniques might fail to detect.

The study, which was made available as a preprint on bioRxiv on 23 September 2026, focuses on the non-coding sections of DNA that are still largely unknown. Although these areas do not produce proteins, they can contain important signals and instructions which have an effect on cell function. The research presents a novel approach to investigating how bacteria handle and control their genetic information.

AI maps previously unexplored genomic regions

The team developed Minerva in order to identify possible interactions between different regions in microbial genomes; rather than depending on similarities with known sequences, Minerva predicts these relationships directly from the DNA by using patterns learned by a genome language model.

On 150 bacterial genomes, Minerva identified a large number of interactions that were not included in the existing annotations. The researchers stated that 84.3 per cent of the predicted intergenic base-pairing interactions were not present in the current annotations, which demonstrates that AI can be of help in generating new ideas in biology.

Unusual RNA structures and viral genetic systems identified

The study also examined a bacterial RNA family known as TwoAYGGAY in Pseudomonas; the model anticipated longer RNA structures and identified associations with repeated DNA sequences, thus providing new insights into how these non-coding elements are organised and how they have evolved.

In a separate section of the study, the researchers examined reverse transcriptase systems associated with bacteriophages, which are viruses that infect bacteria. They identified RNA arrays that maintain their structure but have different sequences and were linked to Unknown Group 27 reverse transcriptases. The findings indicate that these RNAs could function as templates for the production of complementary DNA that is capable of forming hairpin shapes.

The researchers also observed that Minerva was able to detect patterns associated with protein-coding areas, even though it had not been trained to do so. This indicates that genome language models may pick up on biological signals that go beyond what they were intended to identify.

Implications for future genomic research

The fact that artificial intelligence is becoming increasingly important in the field of microbial genomics is shown by the fact that models such as Minerva are able to predict interactions and identify patterns in areas which have not been extensively studied, thus helping researchers to decide what to study next and enabling them to gain a better understanding of biological systems that are still not well understood.

Yet the predictions do not reveal the exact function of each element identified. In order to verify which of the predicted interactions actually take place in living cells and the way in which they affect the microbes, experiments will be necessary. Although the study has undergone peer review, it does nonetheless offer a promising illustration of how machine learning can complement traditional genomics and assist scientists in moving from the identification of known genes to the exploration of the complex relationships that shape microbial life.

More at https://www.biorxiv.org/content/10.64898/2026.09.22.753630v2.full.pdf

Internship in Computational Biology

Thu, 04 Sep 2014 04:19:40 -0500

We are looking for a motivated and autonomous intern to study gene expression in hybrid organisms. The student will work on natural hybrids of two or three different species of fungal endosymbionts of grasses. The pupose of this project is to build software allowing us to identify the genomic origin of expressed genes. To do that, the intern will have to analyze expression data (from RNA-seq) to find SNPs on the sequenced mRNAs allowing to identify from which of the parental genome the expressed gene come from. The data will have to be saved in a database using the standard BioSQL schema.

This job will allow the intern to become more familiar with new biological and bioinformatics tools like next generation sequencing, RNA-Seq data analysis and comparative genomics.

To apply for this position, send the following documents (in PDF format) to Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz):

1. A short cover letter.
2. A curriculum vitae, with transcript details.
3. The names and contact details of two referees willing to provide a confidential letter of recommendation upon request.

Informal enquiries are welcome. Formal applications are due by Sunday 2nd December 2012.
Requirements:

This position requires a good understanding of genetic problems, a good command of at least one scripting language (Perl, Python...), a basic knowledge of MySQL or any relational database management system. Knowledge in biological programming libraries (BioPython, BioPerl, BioRuby...), Java, C++ or any compiled language is an asset but not required. Undergraduate or Master degree is required.
Contact Information:

Dr. Pierre-Yves Dupont
Institute of Molecular BioSciences
Massey University
Private Bag 11 222
Palmerston North 4442
NEW ZEALAND

http://massey.genomicus.com/
p.y.dupont@massey.ac.nz

Information about the Institute of Molecular BioSciences (http://imbs.massey.ac.nz/) and the Computational Biology Research Group (http://massey.genomicus.com/) is available online. For more information about the position, you can contact Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz).

Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'

Yeshodari — Wed, 11 Feb 2015 04:59:57 -0600

Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'

Abstract

Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.

Webinar Details

Sessions	San Francisco Time (PST)	Tokyo Time (GMT+09:00)	Berlin Time (GMT+01:00)	Mumbai Time (GMT+05:30)
Session 1	25 Feb 12:30 AM	25 Feb 5:30 PM	25 Feb 9:30 AM	25 Feb 2:00 PM
Session 2	25 Feb 9:00 AM	26 Feb 2:00 AM	25 Feb 6:00 PM	25 Feb 10:30 PM

Register here: http://www.strand-ngs.com/webinar_registration

About Speaker:

Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.

Please feel free to contact us 24/5, for availing free online training or if you have any questions.

Email: sales@strandngs.com

Phone (USA): 1-800-752-9122

Phone (ROW): +1-650-353-5060

Bioinformatics position at IRCCS Casa Sollievo della Sofferenza

Wed, 10 Sep 2014 14:25:34 -0500

The bioinformatics unit at IRCCS Casa Sollievo della Sofferenza - Mendel laboratory in Rome is looking for one young bioinformatician with specific experience and/or interest in the analysis of genomics and transcriptomic data.

The candidate will be mainly in charge of developing research on Gene Expression/SNP Arrays data, NGS whole -exome and -transcriptome datasets and biological networks in the contexts of genetic diseases, innovative therapies and regenerative medicine. Main activities will be: (i) data analysis (short-reads mapping, genomics aberrations discovery and annotation, variants pathogenicity detection); (ii) functional/pathway enrichment analysis; (iii) biological networks analysis (artificial knockout, redundancy and lethality analysis, gene set essentiality); (iv) developing of ad-hoc software solutions/routines on clusters of CPUs and GPUs.

The correct cultural background (training in Biology / Computer Science / Statistics or a mix of the three) and a strong interest in working in high throughput data analysis will be considered at the same level of specific experience in the above-mentioned fields.

Knowledge of molecular modeling and simulation and willingness to learn one or more of these languages: python, perl, R, Java, C++, C# is a golden plus. Good knowledge of Scientific English will be positively evaluated for this position, together with good presentation and teamwork skills.

Candidates should send:
• a cover letter explaining the role they would like to undertake within the Center, even if it is not listed in this job adv, stating clearly why they would be a good fit to the proposed role, and what they would bring to the Center in terms of expertise, ideas, talent;
• a CV including a list of publications;
• List of referees.

A CV with one professional reference, details on educational background and of the biological and/or bioinformatic and/or data analysis skills and experience should be sent by email for a preliminary selection to: Tommaso Mazza t.mazza@css-mendel.it

kraken: A universal genomic coordinate translator for comparative genomics

Jit — Thu, 07 Dec 2017 04:45:43 -0600

If you planning on conducting a study involving dozens of large genomes, then you do not have to run all pairwise synteny alignments .. simply try kraken: A universal genomic coordinate translator for comparative genomics

Address of the bookmark: https://github.com/nedaz/kraken

URDIP Bioinformatics RA/JRF Vacancies

Sat, 20 Sep 2014 20:52:56 -0500

CSIR - UNIT FOR RESEARCH AND DEVELOPMENT OF INFORMATION PRODUCTS (CSIR- URDIP)

Adv. No. URDIP/ 6/2014

Opportunity for young Bioinformatics Professionals to make a career in the area of Intellectual Property CSIR has set up a Unit for Research and Development of Information Products (CSIR-URDIP) at Pune to work in the area of scientific informatics. One of the major focus areas of research work at CSIR-URDIP is PATENT INFORMATICS. With the increasing applications of Bioinformatics in the areas of life sciences industry such as Agriculture and Health Care (Diagnostics and Drugs), the output of research in these area is being protected by different forms of Intellectual Property rights. Realizing the importance of IP in the Bioinformatics field, Department of Biotechnology (DBT) has sanctioned a project on “Development, Facilitation and Harvesting of Bioinformatics related Intellectual Property” at CSIR-URDIP.

The project will involve application of Patent Informatics tools and techniques to Bioinformatics (including creation of patent landscapes, preparation of techno-legal reports of patentability, freedom to operate studies) to help protect IPRs and develop and conduct training programmes on IPRs related to Bioinformatics.

CSIR-URDIP invites applications from young Bioinformatics professionals to work on this emerging area which offers challenging opportunities and attractive career possibilities in future.

Position I: Research Associate

No of Positions: One

Consolidated amount Payable: Rs. 22,000/- per month + 20% HRA= Rs.26,400

Qualification: PhD in Bioinformatics. In exceptional cases, candidature of M. Tech. candidates with First class in Bioinformatics with three years of relevant work experience will also be considered.

Age Limit: 35 years. The age should not exceed the limit indicated as on a closing date of receipt of completed application form.

Upper age limit is relaxable for 5 years for SC/ST, OBC, Physically handicapped and female candidates as per CSIR/Government of India rules.

Position II: Junior Research Fellow

No of Positions: one

Consolidated amount Payable: Rs. 16,000/- + 20% HRA = 19,200

Qualification: M.Sc / BE or equivalent in Bioinformatics with minimum of 55% marks in aggregate Job requirement: Scientific literature and patent search, analysis and Report Writing

Preference: Preference will be given to candidates with knowledge of patents and or 1-2 years of experience + Knowledge of Computers (MS Excel + Word Processing)

Age Limit: 28 years. The age should not exceed the limit indicated as on a closing date of receipt of completed application form.

For details please visit our website (www.urdip.res.in/careers) for further details and apply online by 30th September, 2014.

Advertisement: http://www.urdip.res.in/download/Advt6_2014.pdf

Scribl : HTML5 canvas genomics graphic library

Jit — Thu, 25 Oct 2018 09:38:53 -0500

Scribl is a javascript, Canvas-based graphics library that easily generates biological visuals of genomic regions, alignments, and assembly data. Scribl can also be used in conventional offline pipelines, since everything needed to generate charts can be contained in a single html file.

Address of the bookmark: http://chmille4.github.io/Scribl/

Arvados

Martin Jones — Sat, 20 Sep 2014 16:54:21 -0500

Arvados is a free and open source bioinformatics platform for genomic and biomedical data. User can Store | Organize | Compute | Share the data for free.

Address of the bookmark: https://arvados.org/

phyloXML: XML for evolutionary biology and comparative genomics

Jit — Sun, 08 Dec 2019 09:41:18 -0600

phyloXML (example) is an XML language designed to describe phylogenetic trees (or networks) and associated data. PhyloXML provides elements for commonly used features, such as taxonomic information, gene names and identifiers, branch lengths, support values, and gene duplication and speciation events. Using these standardized elements allows interoperability between various applications and databases. Furthermore, both due to extensible nature of XML itself and the provision of elements by phyloXML, extensibility as well as domain specific applications are ensured. The structure of phyloXML is described by XML Schema Definition (XSD) language.

http://www.phyloxml.org/archaeopteryx-js/adh.html

Address of the bookmark: http://www.phyloxml.org/

PostDoc Scientist Bioinformatics at CCMB

Fri, 26 Sep 2014 19:58:41 -0500

1. Project Assistant/Junior Research Fellow/ Project Fellow [PA_JRF_PF]

a) M.Sc/or equivalent in biological sciences/related areas [Position Code: PA_JRF_PF_a]
b) B.E/B.Tech/ M.Sc in biotechnology/bioinformatics/computer science/Chemistry/Physics or MCA [Position Code: PA_JRF_PF_b]
c) M.Sc/or equivalent in wildlife sciences/ecology/environmental sciences or MBBS/BVSc/MVSc. [Position Code: PA_JRF_PF_c]

(Candidates with result awaited are NOT eligible to apply)

Upper Age limit 28years

Rs.12000 / Rs.16000 (as sanctioned by the funding agency)

2. Post Doctoral Fellow/Research Associate in multiple research areas [PDF_RA]

Ph.D. (submitted/awarded) in any branch of biological Sciences. Candidates with Ph.D. in other sciences are also encouraged to apply.

Experience in molecular biology, biochemistry, structural biology, cell biology, infectious disease, conservation genetics, veterinary science, reproductive biology, and molecular diagnostics is desired but not mandatory.

[Position Code: PDF_RA]

UpperAge limit 35years

Rs. 22000- 26000 (as sanctioned by the funding agency)

3. Post Doctoral Scientist Fellow [PDSF]

Ph.D in any of the following areas: bioinformatics, next generation sequencing, high throughput data analysis, proteomics, bio-statistics, computer science, information technology, computer hardware and networking/clustering, parallel processing.
[Position Code: PDSF]

Upper Age limit 40 years

Rs. 40000 consolidated (as sanctioned by the funding agency)

Download Application: Last date for apply online: 09th Oct 2014

Advertisement: www.ccmb.res.in//index.php?view=notifications&mid=0&id=71&nid=38

Apply online http://www.ccmb.res.in/positions/temp_notif/online_form.html

More at http://www.ccmb.res.in//index.php?view=notifications&mid=0&id=71&nid=38