<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/43587?offset=40 https://bioinformaticsonline.com/bookmarks/view/44620/diy-transcriptomics Wed, 31 Jul 2024 01:19:26 -0500 https://bioinformaticsonline.com/bookmarks/view/44620/diy-transcriptomics <![CDATA[DIY Transcriptomics]]> A semester-long course covering best practices for the analysis of high-throughput sequencing data from gene expression (RNA-seq) studies, with a primary focus on empowering students to be independent in the use of lightweight and open-source software using the R programming language and the Bioconductor suite of packages. This course follows a hybrid format in which online lectures are paired with in-person labs where students participate in hands-on, live coding exercises using real ‘omic datasets. The course is focused on datasets and topics central to infectious disease research, immunology, and One-Health, but the concepts and approaches covered are applicable to any genomic study.

https://diytranscriptomics.com

Address of the bookmark: https://diytranscriptomics.com

]]> Abhi https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist Fri, 02 Mar 2018 06:54:15 -0600 https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist <![CDATA[Python learning resources for bioinformatics and computational biologist !]]> Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.

Professionally, Python is great for backend web development, data analysis, artificial intelligence, and scientific computing. Many developers have also used Python to build productivity tools, games, and desktop apps, so there are plenty of resources to help you learn how to do those as well.

For pros and cons visit http://www.bestprogramminglanguagefor.me/why-learn-python and http://bioinformaticsonline.com/discussion/view/459/python-vs-perl

More resources at https://github.com/CodementorIO/Python-Learning-Resources

Following are the list of useful python programming resources:

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43042/bioinformatics-in-thailand Wed, 28 Apr 2021 02:04:56 -0500 https://bioinformaticsonline.com/bookmarks/view/43042/bioinformatics-in-thailand <![CDATA[Bioinformatics in Thailand !]]> Our international PhD and master programs are designed for students who desire focused training in the elements of biology, computer science, and information technology needed for a successful career in the exciting new discipline of Bioinformatics & Systems Biology. Students in our program will receive comprehensive training in omics analysis, database design and management, software engineering and programming (including web-based development), simulation techniques and modeling, and data integration. Each student will apply their skills to a practical project, where they will design and implement a solution to a real-world problem under the guidance of an experienced mentor in industry or academia.

https://bioinformatics.kmutt.ac.th/about.html

Duangrudee Tanramluk (Ajarn Wi) uses computational biology and machine learning to tackle the key to drug design problems via MANORAA webserver.

https://mb.mahidol.ac.th/en/bioinformatics/

https://graduate.mahidol.ac.th/inter/

This international Doctorate programme is designed to further broaden students’ knowledge in Bioinformatics and Molecular Biology to their maximum capability. 

http://www.mbb.psu.ac.th/programmes/phd

Ph.D. program in Bioinformatics and Computational Biology is a joint effort of the Faculty of Science and Faculty of Medicine, Chulalongkorn University. The program has study plans for both applicants who hold a bachelor’s degree and applicants who hold a master’s degree in any related fields of study.

http://www.bioinfo.sc.chula.ac.th/ph-d-program-specialization/

Additional detail 

https://www.biotec.or.th/en/index.php/research/research-units/genome-technology-research-unit

https://tbrcnetwork.org/labtbrc/index.php/bioinformatics-and-chemoinformatics/

https://genomicsthailand.com/Genomic/home

Address of the bookmark: https://bioinformatics.kmutt.ac.th/

]]> Shruti Paniwala https://bioinformaticsonline.com/bookmarks/view/43552/understanding-pango-networks Sat, 16 Oct 2021 14:02:36 -0500 https://bioinformaticsonline.com/bookmarks/view/43552/understanding-pango-networks <![CDATA[Understanding pango networks !]]> In the vast majority of instances it is expected that Pango lineage names and designations will conform to the following rules. These rules also act as guidelines for the decisions made by the Lineage Designation Committee.

https://www.pango.network/the-pango-nomenclature-system/statement-of-nomenclature-rules/

https://www.pango.network/how-does-the-system-work/what-are-pango-lineages/

Reference paper

https://www.nature.com/articles/s41564-020-0770-5

Address of the bookmark: https://www.pango.network/the-pango-nomenclature-system/statement-of-nomenclature-rules/

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material Sat, 18 Mar 2023 11:26:18 -0500 https://bioinformaticsonline.com/bookmarks/view/44279/bioinformatics-training-material <![CDATA[Bioinformatics Training Material !]]> Glittr is a curated list of bioinformatics training material.
All material is:

  • In a GitHub or GitLab repository
  • Free to use
  • Written in markdown or similar

NOTE: This list of courses is selected only based on the above criteria.
There are no checks on quality.

https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

Address of the bookmark: https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software Sun, 08 Jun 2014 10:06:26 -0500 https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software <![CDATA[Ten recommendations for creating usable bioinformatics command line software]]> Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author’s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user’s time, and improve the quality of scientific analyses.

Address of the bookmark: http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

]]> RAJESH DETROJA https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics Thu, 18 Dec 2014 11:05:42 -0600 https://bioinformaticsonline.com/bookmarks/view/19636/google-genomics <![CDATA[Google Genomics]]>

  • Explore genetic variation interactively. Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.

  • Process big genomic data easily. Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.

  • Use Google's infrastructure and big data expertise. Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.

  • Support emerging global standards. Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.

    • Address of the bookmark: https://cloud.google.com/genomics/

    ]]>     Tenzin Paul     https://bioinformaticsonline.com/bookmarks/view/32379/enrichr-a-comprehensive-gene-set-enrichment-analysis Thu, 27 Apr 2017 05:42:09 -0500 https://bioinformaticsonline.com/bookmarks/view/32379/enrichr-a-comprehensive-gene-set-enrichment-analysis <![CDATA[Enrichr: a comprehensive gene set enrichment analysis]]> Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

    https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw377

    Address of the bookmark: http://amp.pharm.mssm.edu/Enrichr/

    ]]>     Jit     https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources Tue, 28 Jun 2022 04:08:06 -0500 https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources <![CDATA[List of comparative genomics resources !]]>

    Compare structural and functional annotations of proteins between sequenced genomes.

    View AREs in the human transcriptome and study the comparative genomics of AREs in model organisms.

    Find information about orthologous genes in prokaryotes.

    Search for publicly available QTL data on livestocks and animal species.

    Find information about bovine genomics data.

    A multi-organism web-based resource system designed to easily retrieve, correlate and interpret data across species.

    A database resource of developmentally associated conserved non-coding elements.

    Delineate conserved non-coding blocks from upstream regions of putative orthologous gene pairs from man, mouse, rat, fugu, Mus musculus, Danio rerio, and zebrafish.

    Find coexpressed gene lists and networks in human and mouse.

    Construct phylogenetic tree of microorganisms based on oligopeptide content of their complete proteomes.

    A novel database server that classifies GenBank's dbEST (database of expressed gene sequences) libraries and removes contaminants.

    Find information about the ancestral relationship between genes.

    Provides an overview of the genomic organization of microRNAs and extent of conservation during evolution in different metazoan species.

    Conduct comparative biometric analysis of chromosomes of different organisms.

    Search for Indices of gene and transcripts in human and mouse.

    Search and compare 12 new and old Drosophila genomes.

    Access to whole genome alignments of human, mouse, rat and fish sequences.

    Find eukaryotic paralog/paralogon information.

    Analyze the evolutionary process of overlapping genes when comparing different species.

    The first publicly available system reported to handle inter-species gene mention normalization.

    A web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes.

    Visualize gene indices of human, mouse, Arabidopsis, Zebrafish, Drosophila and Sheep.

    Find information about mutated mouse genes.

    A data management and analysis system for metagenomes

    Search for influenza sequence, vaccine, and drug resistance information.

    LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal models for their research.

    The missing link between multi-species full genome comparisons and functional analysis.

    Conduct comparative analysis of completely sequenced microbial genomes.

    A biologist-centric software for evolutionary analysis of DNA and protein sequences.

    Conduct single nucleotide polymorphisms diversity measurements among homologous sequences from the Mammalia class.

    Find information about 1000s of microbial genomes.

    A database dedicated to the study of genome conservation.

    Explore orthologous relations across 352 complete genomes.

    Browse complete genomes in several clades.

    A database of orthologous genomic markers for placental mammal phylogenetics.

    Conduct genome wide functional and structural analysis.

    Conduct genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes.

    Compare phenotypes of a given gene or gene set in different model organisms.

    Phylemon is a web server that integrates a selected suite of more than 20 different tools from the most popular stand-alone programs of phylogenetic and evolutionary analysis.

    Use this database to see where in the evolution some phylogenetic lineages were started, and over which species they were contained.

    Search for genomic information on nematode satellite species Pristionchus pacificus.

    Find information about related protein sequences.

    Database hosting genomics and post-genomics data from multiple protozoans.

    A database of pseudogene families based on the protein families from the Pfam database.

    Find genomic information about mammals.

    Find information about predicted regulons in prokaryotic transcription regulation.

    Perform systematic comparison of proteome data among species.

    A comparative map viewer dedicated to the biology of the Solanaceae family.

    Analyze data from functional analysis on fragmented microbial genetic material.

    Visualize and explore comparative genomic hybridization data sets.

    Search for genome-wide annotations of regulatory sites in yeast and prokaryotes genomes.

    Search for information on adaptive evolution in gene families of higher plants and chordate.

    Generate graphical maps of circular genomes that show sequence features, base composition plots, analysis results and sequence similarity plots.

    Conduct a comprehensive analysis of genes and genomes.

    An interactive online poster presentation on the Macaque genome, including high-quality images, video clips, and Web resources

    Search for annotated genetic information of expressed sequence tags (ESTs) in different eukaryotic organisms.

    Find mapping and expression information for a unigene cluster (ESTs and full-length mRNA sequences organized into clusters that each represent a unique known or putative gene)

    A public online resource for identifying or designing 'universal' overgo-hybridization probes from conserved sequences that can be used to efficiently screen one or more genomic libraries from a designated group of species.

    Comprehensive suite of programs and databases for comparative analysis of genomic sequences.

    Find metabolic networks and phylogenomic information on a taxonomically diverse range of eukaryotes.

    ]]>     Shruti Paniwala     https://bioinformaticsonline.com/bookmarks/view/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation Mon, 29 May 2017 05:39:29 -0500 https://bioinformaticsonline.com/bookmarks/view/33219/dbcan-a-web-server-and-database-for-automated-carbohydrate-active-enzyme-annotation <![CDATA[dbCAN: a web server and DataBase for automated Carbohydrate-active enzyme ANnotation]]> dbCAN is a web server and DataBase for automated Carbohydrate-active enzyme ANnotation, funded by the BioEnergy Science Center of the DOE. Similar resources on the web include CAZy database and CAT. All data in dbCAN are generated based on the family classification from CAZy database while it has the following unique features compared with CAZy database and CAT:

    • dbCAN provides the capability of automated and comprehensive CAZyme annotation of a given genome submitted by the user;
    • dbCAN provides an explicitly defined signature domain for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced genomes;
    • dbCAN provides the most complete set of metagenomic CAZyme genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;
    • dbCAN provides a subfamily classification of the existing CAZyme families based on sequence similarities;
    • dbCAN make all pre-computed data freely available to the public, including sequence alignments, hidden markov models (HMMs) and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.

    dbCAN is updated regularly when CAZy database created new families based on latest literature.

    Address of the bookmark: http://csbl.bmb.uga.edu/dbCAN/index.php

    ]]>     Jit