<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/39307?offset=80 https://bioinformaticsonline.com/bookmarks/view/34041/r-tuorial Mon, 31 Jul 2017 08:41:40 -0500 https://bioinformaticsonline.com/bookmarks/view/34041/r-tuorial <![CDATA[R tuorial]]> R learning resources

https://flowingdata.com/

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

]]> Rahul Nayak 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/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology Fri, 26 Jul 2024 01:39:14 -0500 https://bioinformaticsonline.com/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology <![CDATA[Online resources on must-read papers in evolutionary biology]]> Online resources on must-read papers in evolutionary biology, for a literature club.

Below is a summary of all answers that we received. All the best, Jana and Xiaoyan 1. *Nick Barton:* - The textbook "Evolution" by Nick Barton, with resources for exploring the literature: Barton, N. H., Briggs, D. E. G., Eisen, J. A., Goldstein, D. B., & Patel, N. H. (2007). Evolution. Cold Spring Harbor Laboratory Press. - Papers from a course named "Classics in Evolutionary Biology": Evolutionary Synthesis 1. Haldane, J. B. S. 1932. The causes of evolution. Longmans. New York. (esp. Ch. IV). 2. Fisher, R. A. 1930. The genetical theory of natural selection. Oxford University Press, Oxford. Selected Sections - Fundamental Theorem. Genetic Variation 1a. Lewontin, R. C., and J. L. Hubby. 1966. A molecular approach to the study of genic heterozygosity in natural populations. II. Amount of variation and degree of heterozygosity in natural populations of Drosophila pseudoobscura. Genetics. 54:595-609. 1b. Sachidandam et al. 2001. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. 409: 928-33. 2. Wright S., Dobzhansky T., Hovanitz W. 1942 Genetics of natural populations VII The allelism of lethals in the third chromosome of Drosophila pseudoobscura. Genetics 27: 363-394. Recombination and evolution 1. Hill, W. G., and A. Robertson. 1966. The effect of linkage on limits to artificial selection. Genet. Res. 8:269-294. 2. Maynard Smith and Haigh. 1974. The hitch-hiking effect of a favourable gene. Genet. Res. 23: 23-35. Understanding sequence variation 1. Begun D. J., Aquadro C. F., 1992 Levels of naturally occurring DNA polymorphism correlate with recombination rate in Drosophila melanogaster. Nature 356: 519-520. 2. Green R. E., Reich D., Pääbo S., 2010 A draft sequence of the Neandertal genome. Science 328: 710-722. Quantitative Genetics: variation in complex traits 1. Galton F., 1877 Typical laws of heredity. Nature 15: 492-495- 512-514- 532-533. 2. Turelli M., 1984 Heritable genetic variation via mutation-selection balance: Lerch's Zeta meets the abdominal bristle. Theor. Popul. Biol. 25: 138-193. Quantitative Genetics: finding the genes 1. Shrimpton A. E., Robertson A., 1988 The Isolation of polygenic factors controlling bristle score in Drosophila melanogaster II Distribution of third chromosome bristle effects within chromosome sections. Genetics 118: 445-459. 2. Boyle E. A., Li Y. I., Pritchard J. K., 2017 An expanded view of complex traits: from polygenic to omnigenic. Cell 169: 1177-1186. Neutral Evolution 1. Kimura, M. 1968. Evolutionary rate at the molecular level. Science. 217:624-626. 2a. Kern A. D., Hahn M. W., 2018 The Neutral Theory in Light of Natural Selection. Molecular Biology and Evolution 110: 21077-6. 2b. Jensen J. D., Payseur B. A., Stephan W., Aquadro C. F., Lynch M., Charlesworth D., Charlesworth B., 2018 The importance of the Neutral Theory in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 112: 2109-4. 2c. Ellegren & Galtier. 2016. Determinants of genetic diversity. Nature Reviews Genetics. Mutation and Genetic Variability 1. Luria, S. E., and M. Delbrück. 1943. Mutations of Bacteria from Virus Sensitivity to Virus Resistance. Genetics. 28(6):491-511. 2. Hill, W G. 1982. "Rates of Change in Quantitative Traits From Fixation of New Mutations." Proceedings of the National Academy of Sciences (U.S.A.) 79: 142-45. Testing for selection 1. McDonald & Kreitman. 1991. Adaptive protein evolution at the Adh locus in Drosophila. Nature. 2. Begun, et al. Mol. Biol. Evol. 16, 1816-1819 (1999). 3. Siddiq et al. 2016. Experimental test and refutation of a classic case of molecular adaptation in Drosophila melanogaster. Nature Ecology & Evolution. The shifting balance 1. Wright, S. 1932. The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proceedings of the VI International Congress of Genetics: 1. pp 356-366. 2. Coyne, J.A., N.H. Barton, and M. Turelli. 1997. A critique of Wright's shifting balance theory of evolution. Evolution 51: 643-671. 3. Barton. 2016. Sewall Wright on Evolution in Mendelian Populations and the "Shifting Balance". Genetics. Evolution of Sex 1. Muller, H.J. 1964. The relation of recombination to mutational advance. Mutation Res. 1(1):2-9 2. McDonald et al. 2016. Sex speeds adaptation by altering the dynamics of molecular evolution. Nature. Kin Selection, Cooperation, and Conflict 1. Hamilton, W. D. 1964. The genetical evolution of social behaviour I. Journal of Theoretical Biology. 7:1-52. 2. Trivers, R. L. 1974 Parent-offspring conflict. American Zoologist. 14(1):249-264. Sexual Selection 1. Zahavi, A. 1975. Mate selection - a selection of a handicap. J. Theor. Biol. 53:205-214. 2. Kirkpatrick, M., and Ryan, M.J. 1991. The evolution of mating preferences and the paradox of the lek. Nature. 350:33-38. Fitness Landscapes 1. Dean, A. 1995. A Molecular Investigation of Genotype by Environment Interactions. Genetics. 139:19-33. 2. Costanzo et al. 2010. The Genetic Landscape of a Cell. Science. Speciation 1. Coyne, J. A., and H. A. Orr. 1989. Patterns of speciation in Drosophila. Evolution. 43:362-381. 2. Corbett-Detig et al. 2013. Genetic incompatibilities are widespread within species. Nature. 2. *Marcos Antezana:* Valen, L. v. 1975. Energy and Evolution. University of Chicago, Department of Biology. 3. *Remco Folkertsma:* 1. The work by Hopi Hoekstra on local adaptation and oldfield mice 2. Poelstra, J. W., Vijay, N., Bossu, C. M., Lantz, H., Ryll, B., Müller, I., ... & Wolf, J. B. (2014). The genomic landscape underlying phenotypic integrity in the face of gene flow in crows. Science, 344(6190), 1410-1414. 4. *Joshka Kaufmann and Leslie Turner* They offer us a link to 'papers every evolutionary biologist should read', the papers are collected by Leslie Turner. https://static1.squarespace.com/static/53e8cb7ce4b02c4bc3aeeee4/t/5ab8fcb670a6ad55c67fcdf4/1522072758665/EvoBioClassicsRefList.pdf 5. *Sarah Stockwell* Matt Ridley collected classic papers in evolutionary biology and printed part of these papers in his book Evolution (see Matt Ridley. Evolution (Univ. of Oxford Press, 2nd edition, 2004)) ]]> BioStar 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