BOL: Related items

Seq: A high-performance, Pythonic language for bioinformatics

Rahul Nayak — Sat, 23 Nov 2019 08:58:12 -0600

Seq is a programming language for computational genomics and bioinformatics. With a Python-compatible syntax and a host of domain-specific features and optimizations, Seq makes writing high-performance genomics software as easy as writing Python code, and achieves performance comparable to (and in many cases better than) C/C++.

Learn more by following the tutorial or from the cookbook.

Address of the bookmark: https://seq-lang.org

Bioinformatics related group

Rahul Agarwal — Sun, 09 Feb 2020 03:17:16 -0600

FaBI emerged from the respective groups of the four founding societies GI (German Informatics Society), DECHEMA (Society for Chemical Engineering and Biotechnology), GBM (Society for Biochemistry and Molecular Biology) and GDCh (German Chemical Society). In fall 2015, the GMDS (German Society for Medical Informatics, Biometry, and Epidemiology) joined FaBI. FaBI represents more than 750 members today and considers itself as a joint representation of interests of bioinformatics research in Germany and as an interlocutor for politics, economy, and society aiming at a strong informatics-based life science research.

Address of the bookmark: https://bioinformatik.de/en/bioinformatics-in-germany/research/research-groups.html

RGCB recruitment notification for bioinformatician !

Tue, 25 Aug 2020 00:25:13 -0500

RGCB Jobs 2020: RGCB released the recruitment notification to hire the candidates who completed B.Tech, M.Sc for 01 Bioinformatician Posts. The eligible candidates can apply for the post through online from 22-08-2020 to 08-09-2020. These selected candidates will be placed as Bioinformatician in Kerala. To know more details such as salary (pay scale), age limit, application fee, application process and more for RGCB recruitment 2020 by clicking apply button.
Organization Name : Rajiv Gandhi Centre for Biotechnology
Post Name : Bioinformatician
No of Vacancy : 01 Posts
Salary : Rs.22,000 (Per Month)
Last Date to Apply : 08-09-2020

More at https://rgcb.res.in/jobs.php

Applied Computational Genomics Course at UU: Spring 2020

Shruti Paniwala — Wed, 23 Dec 2020 03:30:44 -0600

This course will provide a comprehensive introduction to fundamental concepts and experimental approaches in the analysis and interpretation of experimental genomics data. It will be structured as a series of lectures covering key concepts and analytical strategies. A diverse range of biological questions enabled by modern DNA sequencing technologies will be explored including sequence alignment, the identification of genetic variation, structural variation, and ChIP-seq and RNA-seq analysis. Students will learn and apply the fundamental data formats and analysis strategies that underlie computational genomics research. The primary goal of the course is for students to be grounded in theory and leave the course empowered to conduct independent genomic analyses.

Address of the bookmark: https://github.com/quinlan-lab/applied-computational-genomics

Fully funded position as PhD Research Fellow in genomics/bioinformatics

Wed, 03 Feb 2021 04:18:57 -0600

A fully funded position as PhD Research Fellow in genomics/bioinformatics is available at the Section for Genetics and Evolutionary Biology (EVOGENE) at the Department of Biosciences, University of Oslo.

The fellowship will be for a period of 3 years, or for a period of 4 years, with 25 % compulsory work (e.g. teaching responsibilities at the department) contingent on the qualifications of the candidate and the teaching needs of the department.

Starting date no later than October 1, 2021.

More at https://www.jobbnorge.no/en/available-jobs/job/199984/phd-research-fellow-in-genomics-and-bioinformatics

Tech and Bioinformatics roles at Basepaws

Wed, 18 Aug 2021 23:34:25 -0500

Basepaws is an LA-based pet genomics company, quickly growing and focused on feline and canine at-home genetic and biome tests, along with many other projects and products in the works. Thank you for taking a look!

Bioinformatics : https://www.linkedin.com/jobs/view/2681785372/

Engineer: https://www.linkedin.com/jobs/view/2681796993/

Bioinformatics tools for genome assembly !

BioStar — Mon, 24 Jul 2023 07:04:26 -0500

There are numerous genome assembly tools available, each with its strengths and weaknesses. Here is a list of some widely used genome assembly tools as of my last update in September 2021:

SPAdes: An assembler specifically designed for single-cell and multi-cell bacterial genomes, as well as small eukaryotic genomes.
ABySS: A parallelized assembler for large genomes that uses de Bruijn graphs.
Velvet: Another de Bruijn graph-based assembler optimized for short-read sequencing data.
SOAPdenovo: A de Bruijn graph-based assembler designed for short reads, widely used for assembling large and complex genomes.
MaSuRCA: A hybrid assembler that combines data from multiple sequencing technologies, such as Illumina and PacBio.
Canu: A long-read assembler optimized for PacBio and Oxford Nanopore sequencing data.
Flye: A long-read assembler suitable for bacterial and small eukaryotic genomes.
SMARTdenovo: An assembler designed for long reads, particularly suited for PacBio data.
SPAdes Long Read (SPAdesLR): An extension of SPAdes for long-read data, such as those from PacBio or Nanopore.
Minia: An assembler optimized for low memory consumption, suitable for small and medium-sized genomes.
Unicycler: A hybrid assembler that combines short and long reads for circular bacterial genome assembly.
wtdbg2: A de Bruijn graph assembler for long reads, efficient for very large genomes.
Shasta: A long-read assembler that uses the Overlap-Layout-Consensus approach, suitable for PacBio and Nanopore data.
Sparc: An assembler designed to handle noisy long reads from Nanopore sequencing.
CANA: An assembler for metagenomic data, particularly for complex and diverse microbial communities.
Ra Assembler: A metagenome assembler for long reads, designed for highly complex metagenomic samples.

Please note that the field of bioinformatics is constantly evolving, and new assembly tools may have emerged since my last update. Additionally, the performance of these tools can vary depending on the characteristics of the sequencing data and the genome being assembled. When selecting an assembly tool, consider the specific requirements of your project, the available data types, and the computational resources at your disposal. Always refer to the respective tool's documentation and publications for the most up-to-date information and recommendations.

BioKit: a set of tools dedicated to bioinformatics, data visualisation

Neel — Tue, 18 Jun 2024 02:04:39 -0500

BioKit is a set of tools dedicated to bioinformatics, data visualisation (biokit.viz), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis (e.g., biokit.stats). Since R is quite common in bioinformatics, we also provide a convenient module to run R inside your Python scripts or shell (:mod:biokit.rtools module).

Address of the bookmark: https://biokit.readthedocs.io/en/latest/index.html

Bioinformatics Codes Search

Jitendra Narayan — Thu, 15 Aug 2013 11:08:52 -0500

I bet, this website will be your best friend in near future. This helps us to explore the existing open source codes and learn from it.

You can find some useful open source bioinformatics codes for your analysis work. You can use the left bar options to filtere out or narrow down your search result. This webpage can be an useful resource for a beginners bioinformatician as it contain several bioinformatics basics script that are commonly used by biological programmers and biologist.

Stand on the slumped, dandruff-covered shoulders of millions of computer nerds. _/\_

Enjoy the code and research work.

http://code.ohloh.net/search?s=bioinformatics

Address of the bookmark: http://code.ohloh.net/search?s=bioinformatics

Programming language to build synthetic DNA

Jit — Mon, 30 Sep 2013 16:37:24 -0500

A team led by Georg Seelig (http://homes.cs.washington.edu/~seelig/index.html) at University of Washington has developed a programming language for chemistry that it hopes will streamline efforts to design a network that can guide the behavior of chemical-reaction mixtures in the same way that embedded electronic controllers guide cars, robots and other devices. In medicine, such networks could serve as “smart” drug deliverers or disease detectors at the cellular level.

Reference & More @

http://www.nature.com/nnano/journal/vaop/ncurrent/full/nnano.2013.189.html

http://www.washington.edu/news/2013/09/30/uw-engineers-invent-programming-language-to-build-synthetic-dna/

Image source: washington.edu