BOL: Related items

SeqCAT: Sequence Conversion and Analysis Toolbox

Neel — Fri, 14 Jun 2024 14:36:53 -0500

Your all-in-one solution for smooth conversion of sequence coordinates.

Designed for bioinformatics data analysis and daily laboratory work, SeqCAT simplifies sequence coordinate conversion. Extract gene and transcript information, manipulate sequences, and easily validate complex genetic events such as fusions with SeqCAT.

More at https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae422/7683049?login=false

Address of the bookmark: https://mtb.bioinf.med.uni-goettingen.de/SeqCAT/home

DEPARTMENT OF GENETICS, GENOMICS AND BIOINFORMATICS, National Biotechnology Development Agency, Nigeria

BioStar — Wed, 05 Sep 2018 10:48:25 -0500

The Genetics, Genomics & Bioinformatics Department (GBBD) at NABDA is unique, encompassing all facets of modern genetics and bioinformatics research. Trans-disciplinary research being conducted in our laboratories would lead to cures for human diseases; improvements to crop and livestock quality and yield; creation of new technologies with applications to medicine; agriculture; environment; and industry.

Our capacity building activities covers both general and specialized topics in translational genetics, and is designed to better acquaint scientists and clinicians with the tools and technologies of genetics and genomics.

OUR RESEARCH ACTIVITIES INCLUDE:

Biomedical Genetics: investigating genetic and environmental factors contributing to phenotypes with relevance to human health and disease.
Computation and Bioinformatics: develop new approaches for the management, analysis, and modelling of large, complex data sets.
Population and Quantitative Genetics: study of how genetic processes evolve to generate genetic variation in populations of organisms, and the effects on the patterning of variation within and between populations and specie, and
Genetic Engineering and Biotechnology: focuses on the research and innovation for industrial enzymes, biologics and biosimilars production.

https://www.h3abionet.org/nabda

Address of the bookmark: http://www.nabda.gov.ng/departments/genetics-genomics-and-bioinformatics

Senior Bioinformatics Scientist @ Strand Life Sciences -- Bangalore, India

Wed, 02 Jan 2019 09:23:49 -0600

RESPONSIBILITIES
The candidate is expected to work on a variety of projects related to analysis of data from NGS, Mass Spectrometry, Flow Cytometry and other related modalities. The position expects hands-on work and a strong eye for detail. The candidate will be able to contribute to impactful work spanning patient care, clinical research, and new assay and method development.
REQUIREMENTS
A PhD in a quantitative field (statistics, math, bioinformatics, computer science, physics or similar) and work experience or post-doc experience handling high throughout genomics data.
PREFERENCES
Experience in working in inter-disciplinary groups and ability to author research publications are additional desired qualities.
LOCALE
The position is in Bangalore and reports to the Chief Scientific Officer.
HOW TO APPLY
Write to ramesh[at]strandls.com.

poRe: an R package for the visualization and analysis of nanopore sequencing data

Jit — Thu, 23 Nov 2017 09:55:57 -0600

Motivation: The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.

Results: Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.

Availability and implementation: poRe is released as a package for R at http://sourceforge.net/projects/rpore/ . A tutorial and further information are available at https://sourceforge.net/p/rpore/wiki/Home/

Contact:mick.watson@roslin.ed.ac.uk

Address of the bookmark: https://academic.oup.com/bioinformatics/article/31/1/114/2365693

Bioinformatics Training Courses At RASA LSI

RASA Life Sciences — Wed, 06 Nov 2019 00:30:51 -0600

RASA conducts comprehensive Life Science skill development training courses in Pune, India for working professionals, researchers, students and job-seeker. The trainings are crafted meticulously, covering different modules of courses such as Bioinformatics course, In silico Drug Discovery course, Next Generation Sequence data analysis course, Molecular Biology & Life science software development course wherein you learn from industry leaders how to apply these skills in life science & have a command over software developing process by using various methodologies. We conduct in-class training and instructor-led live online classes worldwide, along with corporate and skill development training worldwide.

Workshops are conducted in regular intervals on Drug Designing, Protein Modeling and Simulation, Chemoinformatics, Bioinformatics etc.The workshops are highly beneficial for working professionals, students, researcher for enhancements of the skills in short duration.

kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome

Jit — Fri, 08 Dec 2017 16:48:40 -0600

Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.

Address of the bookmark: https://sourceforge.net/projects/ksnp/files/

Machine learning training and courses in bioinformatics !

Rahul Nayak — Tue, 31 Dec 2019 19:33:07 -0600

Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models and machine learning techniques. We will focus on probabilistic models (Markov models, Hidden Markov models, and Bayesian networks) for biological sequence analysis and systems biology. Other machine learning techniques, such as Naive bayes, neural networks and SVMs will only be covered briefly.

More at http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/

PGAP-X: Extension on pan-genome analysis pipeline

Rahul Nayak — Tue, 23 Jan 2018 11:41:43 -0600

PGAP-X is a microbial comparative genomic analysis platform with graphic interface. Serials of algorithms and methodologies have been developed and integrated to analyze and visualize genomics structure variation, gene distribution with different conservative levels, and genetic variation from pan-genome sight. At the same time, analytical result data from many other programs, including genome alignment result and orthologs clusters, are also supported to be further analyzed or visualized in PGAP-X. The workflow and feature snapshot in PGAP-X were shown as Fig.1 and Fig.2.

Address of the bookmark: https://pgapx.ybzhao.com/

Bioinformatician on Valentine's Day

BioQueen — Sun, 14 Feb 2021 11:36:32 -0600

Once asked to a bioinformatician "How is ur Valentine's Day?"

Bioinformatician replied:
if ($date == "Valentine's Day" && $me =! Bioinformatician) {
rose_day(); promise_day(); kiss_day();
}
else {
hack_genome(); ko-fi(); youtube(); do_scripting(); sleep();
)

bpRNA: large-scale automated annotation and analysis of RNA secondary structure

Rahul Nayak — Wed, 23 May 2018 03:24:33 -0500

bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature.

The bpRNA code is written in perl and requires the Graph perl module. Several additional scripts for analysis are included. The source code is available at http://github.com/hendrixlab/bpRNA.

Address of the bookmark: http://github.com/hendrixlab/bpRNA