<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/28997?offset=1170 https://bioinformaticsonline.com/opportunity/view/42953/ra-bioinformatics-at-sir-ganga-ram-hospital-new-delhi Sun, 14 Mar 2021 10:40:18 -0500 <![CDATA[RA Bioinformatics at Sir Ganga Ram Hospital, New Delhi]]> Opportunities available at Institute of Medical Genetics & Genomics, Sir Ganga Ram Hospital, New Delhi.

1) Senior Research Fellow under ICMR Project: M.Sc. (Life Sciences) with 2 years of experience (preferable in the field of Bioinformatics) or MBBS Degree.

2) Research Associate under ICMR Project: . Ph.D.(Life Science/Biotechnology/Bioinformatics) or equivalent degree or having 3 years of research, teaching and design and development experience after M.Tech with at least one research paper in science Citation Indexed (SCI) Journal.
Work experience in the area of Human genomics/Next Generation Sequencing data analysis/Big data genomics would be preferred.
Application link:

https://sgrh.com/joblist

Post Code: 2023, 2024

]]> https://bioinformaticsonline.com/opportunity/view/43341/nigerian-bioinformatics-and-genomics-network-nbgn Tue, 31 Aug 2021 08:29:40 -0500 <![CDATA[Nigerian Bioinformatics and Genomics Network (NBGN)]]> This is to announce the second official conference of the Nigerian Bioinformatics and Genomics Network (NBGN). October 11-13,2021 at Landmark University, Omu-Aran, Kwara State and Zoom ( conference link to be announced soon

#NBGN21

www.nbgn21conference.com

]]> https://bioinformaticsonline.com/bookmarks/view/42491/eukulele-taxonomic-annotation-of-the-unsung-eukaryotic-microbes Sat, 26 Dec 2020 12:10:17 -0600 https://bioinformaticsonline.com/bookmarks/view/42491/eukulele-taxonomic-annotation-of-the-unsung-eukaryotic-microbes <![CDATA[EUKulele: Taxonomic annotation of the unsung eukaryotic microbes]]>  EUKulele, an open-source software tool designed to assign taxonomy to microeukaryotes detected in meta-omic samples, and complement analysis approaches in other domains by accommodating assembly output and providing concrete metrics reporting the taxonomic completeness of each sample.

Address of the bookmark: https://github.com/AlexanderLabWHOI/EUKulele

]]> Shruti Paniwala https://bioinformaticsonline.com/opportunity/view/43993/phd-positions-on-integrative-omics-and-phylogenomics Wed, 19 Oct 2022 05:11:11 -0500 <![CDATA[PhD positions on integrative omics and phylogenomics]]> 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.

]]> https://bioinformaticsonline.com/file/view/87/linux-cheat-sheet Tue, 09 Jul 2013 17:30:04 -0500 https://bioinformaticsonline.com/file/view/87/linux-cheat-sheet <![CDATA[Linux Cheat Sheet]]> In an attempt to find a good Linux reference for bioinformatician and BOL readers, I was unsuccessful at finding a decent one on the Internet. So, we decided to make a cheat sheet for biological programmers.

]]> Jitendra Narayan https://bioinformaticsonline.com/bookmarks/view/44254/bioinformatics-chat Mon, 13 Mar 2023 13:20:27 -0500 https://bioinformaticsonline.com/bookmarks/view/44254/bioinformatics-chat <![CDATA[Bioinformatics Chat !]]> 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/

]]> BioStar https://bioinformaticsonline.com/news/view/396/bioinformatics-introduction-to-perl Thu, 11 Jul 2013 09:49:37 -0500 https://bioinformaticsonline.com/news/view/396/bioinformatics-introduction-to-perl <![CDATA[Bioinformatics: Introduction to PERL]]> This course is aimed at those new to programming and provides an introduction to programming using Perl. By the end of this course, attendees should be able to write simple Perl programs and to understand more complex Perl programs written by others. The course will be taught using the online Learning Perl materials created by Sofia Robb of the University of California Riverside. Further information is available.

]]> Archana Malhotra https://bioinformaticsonline.com/pages/view/44618/important-bioinformatics-tools Tue, 30 Jul 2024 05:03:29 -0500 https://bioinformaticsonline.com/pages/view/44618/important-bioinformatics-tools <![CDATA[Important Bioinformatics Tools !]]> 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.

]]> BioStar https://bioinformaticsonline.com/opportunity/view/842/ngs-bioinformatics-summit-europe Sat, 13 Jul 2013 17:02:34 -0500 <![CDATA[NGS & Bioinformatics Summit Europe]]> NGS & Bioinformatics Summit Europe

Conference

7th to 8th October 2013
Berlin, Germany

Website: https://www.gtcbio.com/conference/ngseurope-overview
Contact person: Kristen Starkey

We welcome you to join us at GTC’s NGS & Bioinformatics Summit Europe on October 7-8, 2013 in Berlin, Germany.

Organized by: GTC
Deadline for abstracts/proposals: 7th September 2013

]]> https://bioinformaticsonline.com/pages/view/44667/bioinformatics-lecture-notes Tue, 01 Oct 2024 03:45:26 -0500 https://bioinformaticsonline.com/pages/view/44667/bioinformatics-lecture-notes <![CDATA[Bioinformatics Lecture Notes]]> Study Resources for

ECM3413 - Bioinformatics

Contents

 

General Information

Lecture Slides

Past Exam Paper

Continuous Assessments

Suggested Reading List

General Information

bullet This module runs in Semester 2. 
bullet It is taught by Dr Ed Keedwell (Module Coordinator)
bullet Module Descriptor:  ECM3413
bullet Lecture Times: Tuesday 5pm,  171| Thursday, 171
bullet Workshop Times: Wednesday 11am Blue Room (Weeks 29,33 &40)
bullet

Assessment: 2 CAs each worth 15% | 1 Examination worth 70%

  

Lecture Slides (if you have to print slides, to save your ink choose 'print in black and white' on the print menu)

bullet

PPT|PDF| Lecture 1 - Introduction to Bioinformatics (& Biology)
bullet

PPT|PDF| Lecture 2 - Genome Sequences: from fragments to sequences
bullet

PPT|PDF| Lecture 3 - Sequence Alignment 1
bullet

PPT|PDF| Lecture 4 - Global Pairwise Sequence Alignment
bullet

PPT|PDF| Lecture 5 - Local Pairwise Sequence Alignment (Smith-Waterman & BLAST)
bullet

DOC| Workshop 1 - Using BLAST and other Bioinformatics Databases
bullet

PPT|PDF| Lecture 6 - Multiple Sequence Alignment
bullet

PPT|PDF| Lecture 7 - BLAST (in more detail) & FASTA
bullet

PPT|PDF| Lecture 8 - Sequence Alignment Conclusion & Other Sequence Analyses
bullet

PPT|PDF| Lecture 9 - Markov Chains and Intro to Hidden Markov Models
bullet

PPT|PDF| Lecture 10 - Hidden Markov Models
bullet

PPT|PDF| Lecture 11 - Classification in Bioinformatics
bullet

DOC|Workshop 2 - Using See5
bullet

Workshop Data - Part 1 - adult.names | adult.data | adult.test, Part 3 - wdbc.names| wdbc.data
bullet

PPT|PDF| Lecture 12 - Gene Expression Data
bullet

PPT|PDF| Lecture 13 - Decision Trees and Gene Expression Classification
bullet

PPT|PDF| Lecture 14 - Other Methods for Gene Expression Classification
bullet

PPT|PDF| Lecture 15 - Gene Regulation
bullet

PPT|PDF| Lecture 16 - Neural Networks in Gene Expression Analysis
bullet

PPT|PDF| Lecture 17 - Genome Analysis
bullet

PPT|PDF| Lecture 18 - Conclusion/Revision Lecture

 

For some reason best known to itself, my PDF creator doesn't like the slide with the substitution matrix on.  Therefore this has been removed from Lectures 3 and 7 for the PDF copy only - however, more information on these matrices can be found here.

Past Exam Paper

The paper from 2007/8 can be found here.

Continuous Assessments

bullet

PDF|  CA1 - Manual Sequence Alignment
bullet

PDF|Promoter.names|Promoter.data|ML.names|ML.data| CA2 - Data Mining in Bioinformatics

 

Suggested Reading List

General Bioinformatics

<="top">Xiong, J., (2006) Essential Bioinformatics, Cambridge University Press

bullet

Lesk, A.M., (2002) Introduction to Bioinformatics, Oxford University Press
bullet

Higgs, P.G., (2005) Bioinformatics and Molecular Evolution,  Blackwell Publishing
bullet

 

Machine Learning in Bioinformatics

bullet

Baldi, P., Brunak, S., (2001) Bioinformatics: The Machine Learning Approach, MIT Press
bullet

Keedwell, E., Narayanan, A., (2005) Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems, Wiley
]]> LEGE