<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/29603?offset=50 https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools Thu, 03 Nov 2016 08:28:25 -0500 https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools <![CDATA[ART: Set of Simulation Tools]]> ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the 1000 Genomes Project . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. VarSim) for evaluating variant calling tools or methods.

Address of the bookmark: http://www.niehs.nih.gov/research/resources/software/biostatistics/art/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs Fri, 04 Nov 2016 10:48:00 -0500 https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs <![CDATA[R Graphs !!]]> The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!

Address of the bookmark: http://rgraphgallery.blogspot.be/

]]> Jit https://bioinformaticsonline.com/pages/view/35525/linux-commands-cheat-sheet-for-bioinformatics-and-computational-biology-professionals Mon, 05 Feb 2018 18:50:41 -0600 https://bioinformaticsonline.com/pages/view/35525/linux-commands-cheat-sheet-for-bioinformatics-and-computational-biology-professionals <![CDATA[Linux Commands Cheat Sheet for Bioinformatics and Computational Biology Professionals]]> The purpose of this cheat sheet is to introduce biologist and bioinformatician to the frequently used tools for NGS analysis as well as giving experience in writing one-liners.

  • File System
    ls — list items in current directory
    ls -l — list items in current directory and show in long format to see perimissions, size, and modification date
    ls -a — list all items in current directory, including hidden files
    ls -F — list all items in current directory and show directories with a slash and executables with a star
    ls dir — list all items in directory dir
    cd dir — change directory to dir
    cd .. — go up one directory
    cd / — go to the root directory
    cd ~ — go to to your home directory
    cd - — go to the last directory you were just in
    pwd — show present working directory
    mkdir dir — make directory dir
    rm file — remove file
    rm -r dir — remove directory dir recursively
    cp file1 file2 — copy file1 to file2
    cp -r dir1 dir2 — copy directory dir1 to dir2 recursively
    mv file1 file2 — move (rename) file1 to file2
    ln -s file link — create symbolic link to file
    touch file — create or update file
    cat file — output the contents of file
    less file — view file with page navigation
    head file — output the first 10 lines of file
    tail file — output the last 10 lines of file
    tail -f file — output the contents of file as it grows, starting with the last 10 lines
    vim file — edit file
    alias name 'command' — create an alias for a command
  • System
    shutdown — shut down machine
    reboot — restart machine
    date — show the current date and time
    whoami — who you are logged in as
    finger user — display information about user
    man command — show the manual for command
    df — show disk usage
    du — show directory space usage
    free — show memory and swap usage
    whereis app — show possible locations of app
    which app — show which app will be run by default
  • Process Management
    ps — display your currently active processes
    top — display all running processes
    kill pid — kill process id pid
    kill -9 pid — force kill process id pid
  • Permissions
    ls -l — list items in current directory and show permissions
    chmod ugo file — change permissions of file to ugo - u is the user's permissions, g is the group's permissions, and o is everyone else's permissions. The values of u, g, and o can be any number between 0 and 7.
    7 — full permissions
    6 — read and write only
    5 — read and execute only
    4 — read only
    3 — write and execute only
    2 — write only
    1 — execute only
    0 — no permissions
    chmod 600 file — you can read and write - good for files
    chmod 700 file — you can read, write, and execute - good for scripts
    chmod 644 file — you can read and write, and everyone else can only read - good for web pages
    chmod 755 file — you can read, write, and execute, and everyone else can read and execute - good for programs that you want to share
  • Networking
    wget file — download a file
    curl file — download a file
    scp user@host:file dir — secure copy a file from remote server to the dir directory on your machine
    scp file user@host:dir — secure copy a file from your machine to the dir directory on a remote server
    scp -r user@host:dir dir — secure copy the directory dir from remote server to the directory dir on your machine
    ssh user@host — connect to host as user
    ssh -p port user@host — connect to host on port as user
    ssh-copy-id user@host — add your key to host for user to enable a keyed or passwordless login
    ping host — ping host and output results
    whois domain — get information for domain
    dig domain — get DNS information for domain
    dig -x host — reverse lookup host
    lsof -i tcp:1337 — list all processes running on port 1337
  • Searching
    grep pattern files — search for pattern in files
    grep -r pattern dir — search recursively for pattern in dir
    grep -rn pattern dir — search recursively for pattern in dir and show the line number found
    grep -r pattern dir --include='*.ext — search recursively for pattern in dir and only search in files with .ext extension
    command | grep pattern — search for pattern in the output of command
    find file — find all instances of file in real system
    locate file — find all instances of file using indexed database built from the updatedb command. Much faster than find
    sed -i 's/day/night/g' file — find all occurrences of day in a file and replace them with night - s means substitude and g means global - sed also supports regular expressions
  • Compression
    tar cf file.tar files — create a tar named file.tar containing files
    tar xf file.tar — extract the files from file.tar
    tar czf file.tar.gz files — create a tar with Gzip compression
    tar xzf file.tar.gz — extract a tar using Gzip
    gzip file — compresses file and renames it to file.gz
    gzip -d file.gz — decompresses file.gz back to file
  • Shortcuts
    ctrl+a — move cursor to beginning of line
    ctrl+f — move cursor to end of line
    alt+f — move cursor forward 1 word
    alt+b — move cursor backward 1 word
]]> Rahul Nayak https://bioinformaticsonline.com/opportunity/view/40503/3-phd-positions-available-in-the-area-of-bioinformaticscomputational-biology-at-ulsteracuk Thu, 02 Jan 2020 12:41:10 -0600 <![CDATA[3 PhD positions available in the area of Bioinformatics/Computational Biology at ulster.ac.uk]]> 3 PhD positions available in the area of Bioinformatics/Computational Biology, Machine Learning (ML)/Artificial Intelligence (AI), Biomarker Discovery, Stratified/Personalized Medicine in Mental Health, Diabetes and Multimorbidity. Please see details (weblinks) below:

1. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/510894
2. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/511458
3. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/512618

Looking for students with good computational/programming skills (preferable in Linux/Shell, Python and/or R) and knowledge in computational biology and statistics. However, students from more biology oriented background but strong interest to learn bioinformatics and programming are also encouraged to apply.

Informal inquiries are welcomed at: p.shukla@ulster.ac.uk

Dr Priyank Shukla PhD FHEA FCHERP
Lecturer (Asst Prof) in Stratified Medicine (Bioinformatics)

Northern Ireland Centre for Stratified Medicine
Biomedical Sciences Research Institute
University of Ulster (Magee Campus)
C-TRIC Building, Altnagelvin Area Hospital
Glenshane Road, Derry/Londonderry
BT47 6SB, Northern Ireland, United Kingdom

T: +44 28 7167 5690
E: p.shukla@ulster.ac.uk
W: https://www.ulster.ac.uk/staff/p-shukla

]]> https://bioinformaticsonline.com/bookmarks/view/2839/look-up-a-biological-numbers Fri, 23 Aug 2013 03:27:45 -0500 https://bioinformaticsonline.com/bookmarks/view/2839/look-up-a-biological-numbers <![CDATA[Look up a biological numbers]]> Did you ever need to look up a number like the volume of a cell or the cellular concentration of ATP, only to find yourself spending much more time than you wanted on the Internet or flipping through textbooks - all without much success? 

Well, it didn’t happen only to you. It is often surprising how difficult it can be to find concrete biological numbers, even for properties that have been measured numerous times. To help solve this for one and all, BioNumbers (the database of key numbers in molecular biology) was created. Along with the numbers, you'll find the relevant references to the original literature, useful comments, and related numbers. 

To cite BioNumbers please refer to: Milo et al. Nucl. Acids Res. (2010) 38: D750-D753. When using a specific entry from the database it is highly recommended that you also specify the BioNumbers 6 digit ID, e.g. "BNID 100986, Milo et al 2010". 

Address of the bookmark: http://bionumbers.hms.harvard.edu/

]]> Jitendra Narayan https://bioinformaticsonline.com/opportunity/view/24041/junior-bioinformatic-position Wed, 26 Aug 2015 05:35:28 -0500 <![CDATA[Junior Bioinformatic position]]> Junior Bioinformatic position in the laboratory of Inflammation and immunology in cardiovascular pathologies at Humanitas:

We are seeking a highly motivated young PhD student with strong interest in high throughput data analysis.
Detailed descriptions of our recent research activities may be found here:
http://www.humanitas-research.org/condorelli-gianluigi-md-phd/

Position is available starting from October/November. A probationary period of one month will be required.

Please send a CV along with a cover letter stating the reasons for applying and contact details of one or more referees to Dr. Paolo Kunderfranco (paolo.kunderfranco@humanitasresearch.it).

]]> 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/opportunity/view/11528/post-doctoral-research-assistant-in-genetics Thu, 05 Jun 2014 16:01:39 -0500 <![CDATA[Post-doctoral Research Assistant in Genetics]]> Post-doctoral Research Assistant in Genetics
Camden, North London
£31.1K per annum inclusive of London Weighting

This is a fixed term post for 36 months.

We wish to recruit a highly motivated, postdoctoral scientist to carry out a BBSRC funded project in the laboratory of Dr. Denis Larkin. The project is focused on developing and applying new algorithms to study genome and chromosome evolution in birds, mammals and other vertebrate species using whole-genome sequences and existing algorithms. The post holder will use cutting edge computational and laboratory approaches to generate chromosomal assemblies for sequenced genomes, study chromosomal structures and genome differences between bird and other vertebrate species in attempt to identify species- and clade-specific genome signatures.

Applicants must have a Ph.D. and a track record of success, as indicated by first-author publications in international journals. They must possess excellent organisation skills and be capable of individual initiative and of interacting as part of a team. Applicants with extensive practical experience in bioinformatics or computer science, programming, visualization, handling of large data sets, high-performance computing are encouraged to apply. The post will involve collaboration with a wide range of academic partners both within the UK, EU and worldwide. In addition to leading their own project the post holder will have opportunities to contribute to multiple international genome initiatives.

Experience in programming, bioinformatics and comparative genome analysis is essential. Applicants should have a minimum of a degree and preferably a higher degree in a relevant subject.

The Royal Veterinary College has the largest range of veterinary, para-veterinary and animal science undergraduate and postgraduate courses of any veterinary school in the world and is one of the largest veterinary schools in Europe.

Prospective applicants are encouraged to contact Dr. Denis Larkin, Comparative Biomedical Sciences Department on +442071211906 or email: dlarkin@rvc.ac.uk

We offer a generous reward package.

For further information and to apply on-line please visit our website: www.rvc.ac.uk
Job reference CBS-0025-14A

Closing date: 4 July 2014
Interviews are likely to be held in July 2014

We promote equality of opportunity and diversity within the workplace and welcome applications from all sections of the community.

]]> 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/news/view/39606/amity-university-bioinformatics-summer-program-kolkata Tue, 11 Jun 2019 21:27:10 -0500 https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata <![CDATA[Amity University Bioinformatics Summer Program - Kolkata]]> Registrations are now open for the 2019 Summer Bioinformatics Training program at Amity University, Kolkata. The program will focus on introductory topics for life science students. We will review important history, topics and challenges bioinformatics can help address in the context of basic research, discovery and industry.

Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/

]]> eliabrodsky