BOL: Related items

LibsDyogen: Libibrary for comparative genomics

Jit — Wed, 25 Dec 2019 01:32:39 -0600

Library of usual classes and functions written in python and used in the Dyogen team for comparative genomics applications.

Collaborative python library used in the DYOGEN teamfor studying the evolution of gene order in vertebrates.

http://www.ibens.ens.fr/?rubrique43&lang=fr

Address of the bookmark: https://github.com/DyogenIBENS/LibsDyogen

JCVI:Python utility libraries on genome assembly, annotation and comparative genomics

Jit — Tue, 17 Mar 2020 06:19:06 -0500

Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.

https://github.com/tanghaibao/jcvi

More at https://github.com/tanghaibao/jcvi/wiki

Address of the bookmark: https://github.com/tanghaibao/jcvi

gggenomes: A grammar of graphics for comparative genomics

Surabhi Chaudhary — Mon, 01 Feb 2021 14:47:32 -0600

gggenomes is a versatile graphics package for comparative genomics. It extends the popular R visualization packageggplot2 by adding dedicated plot functions for genes, syntenic regions, etc. and verbs to manipulate the plot to, for example, quickly zoom in into gene neighborhoods.

Address of the bookmark: https://github.com/thackl/gggenomes

GEnView: A phylogeny based comparative genomics software to analyze the genetic environment of genes

Abhi — Tue, 28 Dec 2021 01:49:03 -0600

A phylogeny based comparative genomics software to analyze the genetic environment of genes. The user can select one or several taxa and provide one or several reference protein(s). Genomes and plasmids (based on user choice) will be downloaded from the NCBI Assembly/NR database and searched for the respective gene. Alternatively, custom genomes can be provided. User selected stretches (20kbp by default) of the genes genetic environment are extracted, annotated and aligned between all genomes. The sequences are then visualized, enabling comparison of synteny and gene content.

More at https://pubmed.ncbi.nlm.nih.gov/34951622/

Address of the bookmark: https://github.com/EbmeyerSt/GEnView

LoVis4u: Locus Visualisation tool for comparative genomics

LEGE — Tue, 17 Sep 2024 02:30:57 -0500

Description

LoVis4u is a bioinformatics tool for Loci Visualisation.

LoVis4u, a command-line tool and Python API designed for highly customizable and fast visualisation of multiple genomic loci. LoVis4u generates vector images in PDF format based on annotation data from GenBank or GFF files. It is capable of visualising entire genomes of bacteriophages as well as plasmids and user-defined regions of longer prokaryotic genomes. Additionally, LoVis4u offers optional data processing steps to identify and highlight accessory and core genes in input sequences.

https://art-egorov.github.io/lovis4u/

Address of the bookmark: https://github.com/art-egorov/lovis4u

List of useful machine / ai learning resources !

Rahul Nayak — Tue, 30 Mar 2021 08:56:06 -0500

ML cheatsheet !

https://github.com/remicnrd/ml_cheatsheet

Visual AI / ML

https://setosa.io/ev/

Simple and efficient tools for predictive data analysis

https://scikit-learn.org/stable/

Which are the best statistical programming languages to study for a bioinformatician?

Jitendra Narayan — Wed, 10 Jul 2013 14:35:34 -0500

In Bio-informatics based genome sequencing and predicting metabolic pathways research jobs I used Matlab, SAS, SPSS, R and several Bioconductor packages. Matlab had a lot of powerful tools and was easy to use, whereas SPSS is for non-programmers and R need programming skills. I am wondering what other people think is best? or there might not be one specific language but a few that lend themselves best to Bio-informatics work that is math heavy and deals with a large amount of data.

Smyth Lab

Sun, 14 Jul 2013 12:26:18 -0500

Statistical functional genomics in experimental medicine
The genome projects and the accelerated development of high-throughput genomic technologies such as microarrays have revolutionised biology. Making the most of this revolution requires the marriage of researchers from mathematical and biological backgrounds.

Research Area:
Linear models for microarray data
Digital gene expression technologies
Detection of molecular pathways
Bioinformatics resources for medical research

Link @ http://www.wehi.edu.au/faculty_members/professor_gordon_smyth/

Welch Lab

Mon, 15 Jul 2013 18:21:13 -0500

They are based in the Department of Genetics at the University of Cambridge.

The research covers diverse areas of evolutionary biology, and molecular evolution in particular. It combines theoretical and empirical approaches, and particularly evolutionary inference from genome sequence data.

Links @ http://www.gen.cam.ac.uk/research/welch/GroupPage/Home.html

ISCB-Asia 2013 Translational Bioinformatics Conference

Thu, 08 Aug 2013 06:31:32 -0500

ISCB-Asia 2013
Translational Bioinformatics Conference
Seoul, Korea
October 2 - 4, 2013

For more information visit: http://www.snubi.org/TBC2013/