<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/44543? https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial Wed, 21 May 2014 12:50:09 -0500 https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial <![CDATA[A Brief Bioinformatics Tutorial]]> This is about how to use a computer to find what is known about a gene of interest and also how to get new insights about it.

The tutorial is divided in three main parts:

  • In the Sequence part, you will see how to look efficiently for a particular protein sequence, how to blast it against the database of your choice to find homologues, how to perform a multiple alignment of the homologues you've selected and how to edit this alignment.
  • The Structure part is about molecular visualization, homology modeling and structural domain prediction.
  • In the Function part, you will be introduced to you 3 useful servers to investigate the function of a protein. i.e. finding interactors, co-expressed genes, see a phylogenetic profile, easily access papers citing your gene etc ...

During all the three parts, we will use the S. cerevisiae VPS36 protein as an example.

Address of the bookmark: http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html

]]> Jit https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning Fri, 01 Jul 2016 12:57:12 -0500 https://bioinformaticsonline.com/bookmarks/view/28200/machine-learning <![CDATA[Machine Learning !!!]]> In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.

Keep scrolling. Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.

Address of the bookmark: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/

]]> Gudiya Pal https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics Fri, 02 Mar 2018 04:26:38 -0600 https://bioinformaticsonline.com/bookmarks/view/35798/an-introduction-to-applied-bioinformatics <![CDATA[An Introduction to Applied Bioinformatics]]> IAB is primarily being developed by Greg Caporaso(GitHub/Twitter: @gregcaporaso) in the Caporaso Lab at Northern Arizona University. You can find information on the courses I teach on my teaching website and information on my research and lab on my lab website.

 

Address of the bookmark: http://readiab.org/

]]> Jit https://bioinformaticsonline.com/pages/view/42810/bioinformatics-in-africa-part3-mali Sat, 06 Feb 2021 13:28:44 -0600 https://bioinformaticsonline.com/pages/view/42810/bioinformatics-in-africa-part3-mali <![CDATA[Bioinformatics in Africa: Part3 - Mali]]> International Center for Excellence in Research (ICER):

The ICER is a research center composed of the following three programs: 1. The Malaria Research and Training Center ­ Parasitology Group,  2. The Malaria Research and Training Center ­ Entomology Group  3. The SEREFO Group.

The first two programs develop biomedical researches in malaria, Filariasis and Leishmaniasis. The  third program develops biomedical researches in tuberculosis and HIV.

Bioinformatics was introduced recently to the ICER and is constantly growing. The ICER has one  team, headed by Sidy SOUMARE, which supports the three programmes in all their needs in  informatics and bioinformatics. This team can beneficiate from some computational facilities (4  blast servers, 15 other servers and around 200 terminals), but the ICER staff needs some training in  order to be able to administrate these facilities.

Research Interest and Activities: The following are the present areas of research interest: 1. Functional genomics 2. Analysis of microarray data 3. Interaction between the vector and the parasite.

]]> BioStar https://bioinformaticsonline.com/pages/view/42815/bioinformatics-in-africa-part7-tunisia Sat, 06 Feb 2021 21:25:09 -0600 https://bioinformaticsonline.com/pages/view/42815/bioinformatics-in-africa-part7-tunisia <![CDATA[Bioinformatics in Africa: Part7 - Tunisia]]> Institut Pasteur de Tunis (IPT):
The IPT is a research institution founded in 1883. IPT is under the supervision of the Ministry of  Health and is part of the Université El Manar of Tunis (Ministry of high Education). The missions  of the institute are: Public Health Laboratory activities (PHL), Research on infectious diseases, and  R/D on vaccines. Research programs are mainly oriented towards local health problems such as  leishmaniais, viral hepatitis, and scorpion venoms. The   group   of   Bioinformatics   and   Modelling   of   the   IPT   is   hosted   by   the  Laboratoire  d’Immunopathologie Vaccinologie et Génétique Moléculaire  (LIVGM), and exists since the  beginning of 2005. Its present research activities include: genome annotation, EST clustering and  modelling of the host/parasite response to Leishmania infection. It consists of two senior scientists,  two PhD students and one MSc student

Centre de Biotechnology de Sfax (CBS):
Bioinformatics activity started at CBS in 2001 with the setting­up of a research and service unit of  bioinformatics. This unit currently includes one senior researcher, one engineer and four Phd  students. Activities include sequence annotation (service) and three research programs: ab initio  prediction of short eukaryote genes, statistical modelling by Bayesian networks approach of signal  transduction pathways and statistical analysis of human sequence variation data (haplotype  reconstruction and linkage disequilibrium). Activities of the Bioinformatics unit could be found at  the website: http://www.cbs.rnrt.tn/ and the research activity report is available under request to  Bioinformatics@cbs.rnrt.tn. Although the computing facilities are good, there is still a need for  trained human resources to strengthen bioinformatics capacities at CBS, particularly in structural  bioinformatics.

Web site and links: http://www.cbs.rnrt.tn

]]> BioStar https://bioinformaticsonline.com/blog/view/43550/basic-structure-of-snakemake-pipeline-run Thu, 14 Oct 2021 07:01:38 -0500 https://bioinformaticsonline.com/blog/view/43550/basic-structure-of-snakemake-pipeline-run <![CDATA[Basic Structure of Snakemake Pipeline Run !]]> /user/snakemake-demo$ ls
config.json data envs scripts slurm-240702.out Snakefile
  • data = mock data for the snakefile to use
  • Snakefile = name of the snakemake “formula” file
    • Note: The default file that snakemake looks for in the current working directory is the Snakefile. If you would like to override that you can specify it following the -s
      • snakemake -s snakefile.py
  • envs = directory for storing the conda environments that the workflow will use.
  • scripts = directory for storing python scripts called by the snakemake formula.
  • config.json = json format file with extra parameters for our snakemake file to use.
  • cluster.json = json format file with specification for running on the HPC
  • samples.txt = file we will use later relating to the config.json file.

Run the snakemake file as a dry run (the example workflow shown above).

  • This will build a DAG of the jobs to be run without actually executing them.
  • snakemake --dry-run

User can execute rules of interest.

  • snakemake --dry-run all VS. snakemake --dry-run call VS. snakemake --dry-run bwa

Run the snakemake file in order to produce an image of the DAG of jobs to be run.

  • snakemake --dag | dot -Tsvg > dag.svg OR snakemake --dag | dot -Tsvg > dag.svg

Run the snakemake (this time not as a dry run)

  1. snakemake --use-conda
]]> Abhi https://bioinformaticsonline.com/file/view/43701/prepare-for-coding-interview Tue, 11 Jan 2022 06:14:41 -0600 https://bioinformaticsonline.com/file/view/43701/prepare-for-coding-interview <![CDATA[Prepare for Coding Interview !]]> This is a comprehensive guide to prepare for your next coding interview. It's great for recent graduates and has questions and practice materials structured from traditional big tech interview formats.

While it does not include the latest developments in programming since 2019, it nails the core fundamentals in a very comprehensive and accessible way!

Credits to Kaiyu Zhang, with additional material in the appendix sourced from Reddit.

People say that interviews at Google will cover as much ground as possible. As a new college graduate, the ground that I must capture are the following. Part of the list is borrowed from a reddit post: https://www. reddit.com/r/cscareerquestions/comments/206ajq/my_onsite_interview_experience_at_google/ #bottom-comments.

1. Data structures

2. Trees and Graph algorithms

3. Dynamic Programming

4. Recursive algorithms

5. Scheduling algorithms (Greedy)

6. Caching 1

7. Sorting

8. Files

9. Computability

10. Bitwise operators

11. System design

]]> Abhi 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