BOL: Related items

Job offer for a postdoctoral researcher in genomics / bioinformatics (2 years)

Fri, 22 Oct 2021 04:44:33 -0500

Ongoing research in the group of Karine Van Doninck involves topics at the core of
evolutionary biology, including the evolution of sex, genome maintenance,
recombination and extreme stress resistance on different eukaryotic systems,
including rotifers, amoeba and Corbicula clams. We are employing different tools
(including experimental ecology, population genetics, phylogeny, comparative
genomics, transcriptomics, bioinformatics, molecular and cellular biology) to study
evolutionary processes at the level of populations, both experimental and natural, and
genomes.

Offer
We offer a full-time contract for two years. The contract starts between October 2021
and December 2021. The position involves no or extremely light teaching load, if the
candidate is interested. Salaries are competitive at the European level. The recruited
person will benefit from the Belgian social insurance scheme (health care, etc.) without
additional expenses.

Profile
Applicants are expected to show outstanding commitment to research and must have
obtained a PhD by the start of the position. A strong expertise in genomics is required.
More specifically, solid competences in bioinformatics (e.g. scripting pipelines) and in
genome evolution are needed. Knowledge or interest regarding recombination,
metazoan evolution, phylogenomics and population genomics is an added-value.

Application
Applications should be submitted via email to karine.van.doninck@ulb.be. The
application package should contain the following documents:
- A curriculum vitae with the complete list of publications
- A cover letter mentioning why the candidate is interested in the position
- Minimum 2 recommendation letters
Interviews: Interviews will be conducted with the selected candidates. Selected
candidates could also be invited to give a seminar to MBE ULB.
For any additional information, please contact karine.van.doninck@ulb.be

2013 NextGen Genomics & Bioinformatics Technologies (NGBT) Conference, New Delhi, INDIA

Thu, 08 Aug 2013 16:21:16 -0500

2013 NextGen Genomics & Bioinformatics Technologies (NGBT) Conference

SciGenom Research Foundation (SGRF) and Institute of Genomics and Integrative Biology (IGIB) are pleased to host the Next-Generation Sequencing and Bioinformatics for Genomics & Healthcare conference.

In the ten years since the first human reference genome was completed for US$3 billion the sequencing technologies have radically changed leading to great reduction in sequencing cost. Today a human genome can be sequenced for under US$ 5000 in less than two weeks. It is expected that by the end of 2015 the cost of sequencing a human genome will drop to below thousand dollars. The next generation sequencing technologies over the past five years have enabled a large number of genomic studies that impact human health and disease. Also, this has made possible the growth of microbial, animal and plant genomics studies. While the data production has increased at a rapid pace challenges remain in analyzing and understanding the data. The conference will cover the next generation sequencing (NGS) technologies, bioinformatics for NGS and applications of NGS in many areas including personalized medicine.

For more info : http://www.scigenomconferences.com/2013/default.php

PhD positions on integrative omics and phylogenomics

Wed, 19 Oct 2022 05:11:11 -0500

Would you like to participate in an exciting interdisciplinary research project to discover the hidden chemistry of plants and its evolution using computational omics approaches? Do you enjoy collaboration and teamwork while being at the cutting edge of scientific progress? We are looking for two PhD candidates with complementary skills to pioneer new technologies to analyze, explore and leverage the diversity of plant chemistry hidden in plant genomes.

Plants represent an untapped resource of natural bioactive compounds that significantly contribute to plant resilience to pathogens, herbivores, and abiotic stresses, and may be applied for medicine or crop protection. In this project, you will design and/or apply innovative omics integration strategies for genomics, transcriptomics, and metabolomics data, to discover plant specialized metabolite biosynthetic pathways and study their evolution. You will work together with the other PhD candidate in this project, which will entail a combination of algorithm development, greenhouse experiments, integrative omics analysis, and evolutionary genomics. Extensive local and international collaboration is foreseen, including possibilities for a foreign research visit as part of your PhD project.

The research is embedded within the chairs of Bioinformatics and Biosystematics. The projects will be (co-)supervised by Dr. Marnix Medema, Dr. Justin van der Hooft, Dr. Klaas Bouwmeester and Prof. Dr. Eric Schranz.

We ask

We are looking for two enthusiastic and complementary team players with all or a subset of the following skills:

a solid academic record (MSc) in bioinformatics, biology, or biotechnology
experience in computational omics analysis and proficiency in programming (in, e.g., Python)
at least basic to intermediate statistical and mathematical skills
demonstrable experience in working with next-generation sequencing data or with greenhouse experiments with plants
affinity with plant science, metabolism and/or biosynthetic pathways
you meet all the entry requirements of the WUR PhD programme.
More information

For more information about this position, please contact Marnix Medema, Associate Professor Bioinformatics, by email (marnix.medema@wur.nl).
For more information about the procedure, please contact vacaturemeldingen.psg@wur.nl.

Postdoctoral Associate - Bioinformatics at Duke University Medical Center

Sat, 10 Aug 2013 18:38:38 -0500

The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.

Bioinformatics Chat !

BioStar — Mon, 13 Mar 2023 13:20:27 -0500

The bioinformatics chat is a podcast about computational biology, bioinformatics, and next generation sequencing.

The bioinformatics chat is produced by Roman Cheplyaka and hosted by Roman and Jacob Schreiber.

Address of the bookmark: https://bioinformatics.chat/

What are the difference between BioRuby and BioGem?

Neel — Mon, 12 Aug 2013 09:27:57 -0500

I came across two diferent but matching term BioRuby and BioGem. What are the difference between these two term? If both are using same Ruby language for development then why did they develope two different biological packages.

Important Bioinformatics Tools !

BioStar — Tue, 30 Jul 2024 05:03:29 -0500

1. Ktrim: An extra-fast, accurate adapter trimmer for sequencing data. It processes FASTQ files from multiple lanes with minimal mismatching and over-trimming of adapters.

2. BWA MEM: A reliable alignment tool (particularly for mapping ALT contigs and HLA genes, which are not fully addressed in BWA-MEM2).

3. Sambamba markdup: Quickly marks or removes duplicate reads using Picard's criteria.

4. ichorCNA: Estimates the tumor DNA fraction in cell-free DNA from ultra-low-pass whole genome sequencing (0.1x coverage) based on copy number alterations (CNA).

5. Fragle: A deep learning method for quantifying ctDNA levels from cell-free DNA fragmentomic profiles. It detects TF as low as ~1% ctDNA and works with targeted genomic panel sequencing data.

6. AlfredQC: A quality control tool for high-throughput sequencing data. It assesses metrics like read quality scores, GC content, and duplication rates, visualized through detailed plots and summary statistics.

7. Mosdepth: A fast tool for calculating sequencing coverage depth, offering a quicker alternative to samtools/sambamba depth by processing BAM and CRAM files.

8. Bedtools: A versatile toolkit for genomics, enabling operations like intersect, merge, count, and shuffle on genomic intervals across formats such as BAM, BED, GFF/GTF, and VCF.

9. Datamash: A command-line tool for basic numeric, textual, and statistical operations on input data streams. It supports operations such as grouping, sorting, transposing, and performing arithmetic calculations on tabular data.

10. gwf.app: A pragmatic alternative to Snakemake. Developed at Aarhus University, this flexible, generic workflow tool builds and runs large scientific workflows.

Computational Biology in the 21st Century: Making Sense out of Massive Data

Thu, 29 Aug 2013 08:32:26 -0500

Computational Biology in the 21st Century: Making Sense out of Massive Data Air date: Wednesday, February 01, 2012, 3:00:00 PM Category: Wednesday Afternoon Lectures Description: The last two decades have seen an exponential increase in genomic and biomedical data, which will soon outstrip advances in computing power to perform current methods of analysis. Extracting new science from these massive datasets will require not only faster computers; it will require smarter algorithms. We show how ideas from cutting-edge algorithms, including spectral graph theory and modern data structures, can be used to attack challenges in sequencing, medical genomics and biological networks. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. Author: Dr. Bonnie Berger Runtime: 00:58:06 Permanent link: http://videocast.nih.gov/launch.asp?17563

Bioinformatics Lecture Notes

LEGE — Tue, 01 Oct 2024 03:45:26 -0500

Study Resources for

ECM3413 - Bioinformatics

Contents

General Information

Lecture Slides

Past Exam Paper

Continuous Assessments

BINC (BioInformatics National Certification) Website address

Kamalakshi Mukherjee — Wed, 14 Aug 2013 09:40:22 -0500

BINC (BioInformatics National Certification) is an initiative of Department of Biotechnology(DBT), Government Of India in coordination with Bioinformatics Center, University of Pune. The objective of the examination is to recognize trained manpower in the area of Bioinformatics. Currently, various Indian universities, Government and private institutions are involved in imparting courses in Bioinformatics in India.

Foreign nationals intending to have certification are eligible to appear for BINC examination.
Minimum qualification includes a degree from a recognized university/institute in the areas listed in FAQ.
Formal training in the area of Bioinformatics is not a prerequisite.
Note that the foreign students will only be certified by DBT and are not eligible for the cash award as well as junior research fellowship.

Address of the bookmark: http://binc.scisjnu.ernet.in/

	This module runs in Semester 2.
	It is taught by Dr Ed Keedwell (Module Coordinator)
	Module Descriptor: ECM3413
	Lecture Times: Tuesday 5pm, 171\| Thursday, 171
	Workshop Times: Wednesday 11am Blue Room (Weeks 29,33 &40)
	Assessment: 2 CAs each worth 15% \| 1 Examination worth 70%

	PPT\|PDF\| Lecture 1 - Introduction to Bioinformatics (& Biology)
	PPT\|PDF\| Lecture 2 - Genome Sequences: from fragments to sequences
	PPT\|PDF\| Lecture 3 - Sequence Alignment 1
	PPT\|PDF\| Lecture 4 - Global Pairwise Sequence Alignment
	PPT\|PDF\| Lecture 5 - Local Pairwise Sequence Alignment (Smith-Waterman & BLAST)
	DOC\| Workshop 1 - Using BLAST and other Bioinformatics Databases
	PPT\|PDF\| Lecture 6 - Multiple Sequence Alignment
	PPT\|PDF\| Lecture 7 - BLAST (in more detail) & FASTA
	PPT\|PDF\| Lecture 8 - Sequence Alignment Conclusion & Other Sequence Analyses
	PPT\|PDF\| Lecture 9 - Markov Chains and Intro to Hidden Markov Models
	PPT\|PDF\| Lecture 10 - Hidden Markov Models
	PPT\|PDF\| Lecture 11 - Classification in Bioinformatics
	DOC\|Workshop 2 - Using See5
	Workshop Data - Part 1 - adult.names \| adult.data \| adult.test, Part 3 - wdbc.names\| wdbc.data
	PPT\|PDF\| Lecture 12 - Gene Expression Data
	PPT\|PDF\| Lecture 13 - Decision Trees and Gene Expression Classification
	PPT\|PDF\| Lecture 14 - Other Methods for Gene Expression Classification
	PPT\|PDF\| Lecture 15 - Gene Regulation
	PPT\|PDF\| Lecture 16 - Neural Networks in Gene Expression Analysis
	PPT\|PDF\| Lecture 17 - Genome Analysis
	PPT\|PDF\| Lecture 18 - Conclusion/Revision Lecture

	PDF\| CA1 - Manual Sequence Alignment
	PDF\|Promoter.names\|Promoter.data\|ML.names\|ML.data\| CA2 - Data Mining in Bioinformatics

	Lesk, A.M., (2002) Introduction to Bioinformatics, Oxford University Press
	Higgs, P.G., (2005) Bioinformatics and Molecular Evolution, Blackwell Publishing

	Baldi, P., Brunak, S., (2001) Bioinformatics: The Machine Learning Approach, MIT Press
	Keedwell, E., Narayanan, A., (2005) Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems, Wiley