<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/44614?offset=30 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/43243/interactive-bioinformatics-resources Thu, 12 Aug 2021 00:09:00 -0500 https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources <![CDATA[Interactive Bioinformatics Resources !]]> Learn how to use bioinformatics tools right from your browser.
Everything runs in a sandbox, so you can experiment all you want.

More at sandbox.bio

Address of the bookmark: http://sandbox.bio

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials Mon, 09 May 2022 05:20:41 -0500 https://bioinformaticsonline.com/bookmarks/view/43863/snakemake-tutorials <![CDATA[Snakemake Tutorials !]]> A lesson introducing the Snakemake workflow system for bioinformatics analysis.

Prerequisites

This is an intermediate lesson and assumes learners have already done some bioinformatics:

  • Familiarity with the BASH command shell, including concepts like pipes, variables and loops.
  • Knowledge of bioinformatics fundamentals like the FASTQ file format and transcriptome sequencing, in order to understand the example workflow.

No previous knowledge of Snakemake or workflow systems is required.

https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/index.html

Address of the bookmark: https://carpentries-incubator.github.io/snakemake-novice-bioinformatics/aio/index.html

]]> Rahul Nayak https://bioinformaticsonline.com/file/view/29601/statistics-using-r-with-biological-examples Thu, 03 Nov 2016 04:55:41 -0500 https://bioinformaticsonline.com/file/view/29601/statistics-using-r-with-biological-examples <![CDATA[Statistics Using R with Biological Examples]]> This book is a manifestation of my desire to teach researchers in biology a bit more about statistics than an ordinary introductory course covers and to introduce the utilization of R as a tool for analyzing their data. My goal is to reach those with little or no training in higher level statistics so that they can do more of their own data analysis, communicate more with statisticians, and appreciate the great potential statistics has to offer as a tool to answer biological questions.

This is necessary in light of the increasing use of higher level statistics in biomedical research. I hope it accomplishes this mission and encourage its free distribution and use as a course text or supplement.

K Seefeld, May 2007

]]> Neel https://bioinformaticsonline.com/blog/view/44871/10-books-to-kickstart-and-level-up-your-bioinformatics-journey Tue, 12 Aug 2025 03:50:11 -0500 https://bioinformaticsonline.com/blog/view/44871/10-books-to-kickstart-and-level-up-your-bioinformatics-journey <![CDATA[10 Books to Kickstart (and Level Up) Your Bioinformatics Journey]]> If you’re starting out in bioinformatics or looking to sharpen your computational biology skills, having the right learning resources makes all the difference.
Here’s my curated list of 10 must-read books — from beginner-friendly introductions to advanced computational genomics.

1️⃣ Data Analysis for the Life Sciences
A fantastic starting point to learn statistics, R programming, and exploratory data analysis in the context of biology. The best part? It’s available free online from HarvardX.

2️⃣ Practical Computing for Biologists
The very first book I picked up when I started learning computational biology. It’s beginner-friendly and focuses on essential computing skills every biologist needs.

3️⃣ A Primer for Computational Biology
An open-access, hands-on introduction to computational biology concepts and coding techniques. Perfect if you want to learn through real examples.

4️⃣ Computational Genomics with R
For those who already know R and want to dive deeper into genome-scale data analysis, from sequence alignment to gene expression.

5️⃣ The Biologist’s Guide to Computing
Bridges the gap between biological problems and computational thinking, making it easier for life scientists to approach programming and data analysis.

6️⃣ Bioinformatics Data Skills
A must-read to sharpen your bioinformatics toolkit — from command-line skills to reproducible research workflows. Ideal once you’ve covered the basics.

7️⃣ Bioinformatics Workbook
A practical tutorial series to help scientists design bioinformatics projects, analyze data, and understand best practices.

8️⃣ Modern Statistics for Modern Biology
An essential guide to modern statistical methods applied to biology, blending theory with hands-on examples in R.

9️⃣ Algorithms on Strings, Trees, and Sequences by Dan Gusfield
A classic reference for anyone wanting to understand the algorithms behind sequence alignment, genome assembly, and biological data structures.

]]> Neel https://bioinformaticsonline.com/blog/view/43983/must-read-paper-and-books-in-evolution-biology Wed, 05 Oct 2022 18:33:01 -0500 https://bioinformaticsonline.com/blog/view/43983/must-read-paper-and-books-in-evolution-biology <![CDATA[Must read paper and books in evolution biology !]]> 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))]]> Abhi https://bioinformaticsonline.com/news/view/6896/dna-tale-of-3-to-4-years-old-serbia-boy Tue, 26 Nov 2013 17:34:00 -0600 https://bioinformaticsonline.com/news/view/6896/dna-tale-of-3-to-4-years-old-serbia-boy <![CDATA[DNA tale of 3 to 4 years old Serbia boy]]> The genome of a young boy found underground at Mal’ta near Lake Baikal of eastern Siberia around 24,000 years ago came out as close relative of Europeans and Native Indians.

Link:

http://www.nytimes.com/2013/11/21/science/two-surprises-in-dna-of-boy-found-buried-in-siberia.html?_r=0

 

http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12736.html

]]> Rahul Agarwal https://bioinformaticsonline.com/videolist/watch/4962/bionics-transhumanism-and-the-end-of-evolution-full-documentary Fri, 27 Sep 2013 11:54:17 -0500 https://bioinformaticsonline.com/videolist/watch/4962/bionics-transhumanism-and-the-end-of-evolution-full-documentary <![CDATA[Bionics, Transhumanism, and the end of Evolution (Full Documentary)]]> Bionics, Transhumanism, and the end of Evolution (Full Documentary) . 2013 This documentary and the rest of the documentaries presented relate to important times and figures in history, historic places and sites, archaeology, science, conspiracy theories, and education. The Topics of these video documentaries are varied and cover ancient history, Rome, Greece, Egypt, science, technology, nature, planet earth, the solar system, the universe, World wars, Battles, education, Biographies, television, archaeology, Illuminati, Area 51, serial killers, paranormal, supernatural, cults, government cover-ups, corruption, martial arts, space, aliens, ufos, conspiracy theories, Annunaki, Nibiru, Nephilim, satanic rituals, religion, strange phenomenon, origins of Mankind]]> https://bioinformaticsonline.com/videolist/watch/6232/the-cat-evolution-domestication-and-genome-10k Sun, 10 Nov 2013 14:33:56 -0600 https://bioinformaticsonline.com/videolist/watch/6232/the-cat-evolution-domestication-and-genome-10k <![CDATA[The Cat: evolution, domestication and Genome 10k]]> A public lecture by Dr Stephen J O'Brien at the UCD Earth Institute, University College Dublin, Ireland. Dr O'Brien is a world leading molecular biologist and dedicated conservationist who uses the tools of molecular biology to help protect endangered species and understand devastating diseases such as cancer and AIDS. He received his PhD in Genetics from Cornell University, USA, in 1971. He then joined the prestigious National Cancer Institute, National Institutes of Health as a post-doc in 1971 and, there, served as Founder and Chief of the Laboratory of Genomic Diversity from 1986-2011. In December 2011, he joined the Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, Russia, as Chief Scientific Officer. Convinced of the utility of exploring diverse species to advance our understanding of the human genome, Dr O'Brien and his team have assembled over 62,000 animal and 424,000 human tissue/DNA specimens, facilitating wide-ranging studies of disease gene associations, species adaptation and natural history. His research interests and expertise span human and comparative genomics, genetic epidemiology, HIV/AIDS, retro-virology, bioinformatics biodiversity and species conservation. Dr O'Brien is best known for documenting the remarkable genetic uniformity of African cheetahs, resolving the mammalian tree of life, describing heretofore unrecognized species of Orangutans, African forest elephants, and Bornean clouded leopards. He is credited with the discovery of CCR5 delta 32, the first of 20 human AIDS restriction genes, which imparts natural immunity to HIV. He is the one of the founders of the Genome 10K initiative, has published over 750 leading research papers, written multiple books and is adjunct professor in over 12 international leading universities. The UCD Earth Institute, University College Dublin, is a multidisciplinary research and education centre with a focus on creating and sharing new knowledge. We aim to contribute to sustainable solutions for many of the pressing Earth-related problems affecting societies now and in the near future.]]> https://bioinformaticsonline.com/researchlabs/view/11107/the-minerva-research-group-for-bioinformatics Tue, 27 May 2014 15:48:14 -0500 <![CDATA[The Minerva Research Group for Bioinformatics]]> The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.

http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27

Kelso Group
Department of Evolutionary Genetics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
Germany
Phone: +49 341 3550 500

Job:
http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40

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