Welcome to LearnBioinformatics!

So I'm planning on applying for a MS Bioinformatics degree in my country and the program listed several foundation subjects that will be tested via a diagnostic exam when I apply. The thing is, I come from a biology background and these subjects have not been tackled at all or in depth in my undergrad. The subjects that I am most concerned with are:

1. Calculus & Matrix Algebra
2. Probability & Statistics
3. Computer Programming (Basic Programming, Programming Constructs, Programming Logic)

Can anyone recommend me resources such as textbooks that I can study in the meantime? Or perhaps even a a specific list of topics within these subjects that might be required in Bioinformatics (since Calculus & Matrix Algebra covers a wide range of topics)? Any help would be greatly appreciated. Thanks!

Hi everyone I'm yara and I'm biotechnologist in my fourth year, l want to start learning bioinformatics,l already learnt python and some basics and i'd love to have a study partner to learn bioinformatics and encourage each other i'm female so i hope i find a girl that have the same passion as well

Hello everyone. How can I remove ions from protein in Biovia Discovery Studio? Creating maps in Autodock is difficult when my protein contains Se ions

i've been trying to use an experimental module called Biopython for a personal project. however it throws out a warning: BiopythonExperimentalWarning: Bio.codonalign is an experimental module which may undergo significant changes prior to its future official release.

warnings.warn(

how do fix this?

Hello guys. I require a little assistance with downloading the Biopython module on Python3 to read a FASTA file. My initial intention was to download straight from the web: https://biopython.org/wiki/Download but it gets a lil more complicated for me personally because it seems i can download by using the "pip install Biopython" syntax

since im new to the language i don't seem to figure out how to configure and import the module into my program. so if you could please dumb it down just a bit just so a fellow beginner cs student would understand, it would make my day a whole lot better. thanks!

Hi guys,

I saw that many students, want to learn some bioinformatics concepts quickly, so I started building this Bioinformatics Quiz youtube channel. I am just putting 5 questions by video, to not be boring.

The channel still very new, it would be great if you could give your feedback.
https://www.youtube.com/@bioinfoReels

Thanks.

Hello everyone! So I am currently doing bachelor's in computer applications, and want to pursue bioinformatics. But since it's not a widely known field, I am not getting quality resources. I am getting confused with the topics (sequencing, epigenetics, transcriptomics etc). I mean this field seems so vast and with so many applications that I am completely lost. Can someone just categorise things for me and advice me where to get started and some noob level projects I can do to get my hand dirty? Thank you!

I am not particularly looking for a specific course or wtvr. I just wanna know some good courses on coursera that can teach me bioinformatics and some of the softwares in details and are actually helpful. Thanks in advance.

sooooo, I'm currently pursuing post grads in bioinformatics and I need help. I want to start working on a project or internship or something that I can add in my resume. In the future I particularly want to work as a genome analyst or something. Can anyone help me out and let me know what lind of skills should I be working on? and what kind of project I should start working on? Also, what are my options, career wise, after studying bioinformatics??????

Hi all!! I’m going to be doing my masters in bioinformatics in the next academic year (2025/26). Was wondering what things should I do to prep myself so that I don’t fall behind with all the tech side of the degree since I come from a biomedical science undergrad.

Hi everyone from the r/learnbioinformatics subreddit! 😃

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Cross posted.

Hello all, I am looking for a bioinformatics course for conservation science (preferably online of course). Does anybody have any leads? I work on mammals, and I am basically a total nincompoop at bioinformatics. I need a course which will help with the following topics, in descending order of importance:

1. Whole genome assembly
2. From fecal/degraded DNA
3. lcWGS datasets
4. Functional genomics would be a bonus

I already have an idea that I will most likely be using tools like ANGSD. Something adjacent to paleogenomics would probably work.

Free or cheap stuff would be great! I already know about Physalia.

Thanks in advance!

I’m really into bioinformatics, but I recently started a job related to clinical trial data analysis, where a specialization in biostatistics would greatly benefit my professional career. Because of this, I’m interested in pursuing a master’s program that focuses on both fields. Additionally, since I started this job, I’d only be able to enroll in an online master’s program.

I would appreciate the community’s opinion on this path and any recommendations for master’s programs that meet these characteristics.

Hey everyone! How's it going?

My name is Felipe, I'm 26 years old, and I'm finishing my degree in Systems Analysis and Development. Although my background is more focused on IT, I've always been passionate about science, especially biological areas and data analysis. Recently, while researching potential fields for a master's degree, I came across Bioinformatics and found it really intriguing.

However, I'm a bit unsure because, despite having a solid foundation in IT, my knowledge of biology—especially in topics like genetics and protein structures—is almost nonexistent.

Currently, I work at a biologicals company called Lallemand, where we deal with studies of bacteria and fungi for the development of biofungicides, among other things. This environment gives me some exposure to professionals in the biological field, which I consider an advantage.

Given this context, I'm wondering if it makes sense and if it's feasible to direct my studies toward Bioinformatics, even with my more technical IT background. Is it worth starting to invest time and energy in learning the necessary biological concepts? And besides the content available on YouTube and the internet, would you recommend any other resources or guidance for someone just starting out?

I appreciate any advice or insights you can share!

Hi all, is there any article which explains the MD simulation of nano particles or if anybody have performed the same can help me with getting started.

Hi there, I am 36 and have a BS in Biology. I have been a specialty practice veterinary technician for about 15 years (licensed since 2019). As with a lot of others in the industry, I am seeking a change and am interested in bioinformatics. Does anyone have any advice or guidance in how best to get into the field? I'm all for self study, formal education programs, apprenticeships, etc.

Any information is greatly appreciated!

Hi everyone,

I would like to do cloud archiving for genome data (sequencing and its metadata), any idea about the best approach?

Thank you

Hi everyone, I did bioinformatics works and learnt them like 3 years ago and lost touch with it. Now, I want to restart my learning in bioinformatics and keeping myself updated. What are some of the courses you recommend and how do you update with the current researches. Can you suggest media pages, websites, podcasts, blogs that help you keep updated. I also would like courses to relaearn all techniques and algorithms and apps used in bioinformatics

Warning: LONG THREAD!!!

Hey everyone! I'm an E&C engineering graduate who transitioned into the biomedical sciences for my Masters degree. Throughout my program, I struggled to pick up foundational concepts, and it took longer for me to gather the knowledge and understanding required to pick a career path after my program. It took me a while to realize that I was better off doing a Masters in Bioinformatics as my skillset better matched the profile needed for a bioinformatician's role. I've been learning skills to strengthen my profile for a grad school program in bioinformatics. While plenty of resources are available, both on this subreddit and on r/bioinformatics, I've learned that what skills one must focus on depends purely on the end goal one wants to serve. After some research and scouring different threads, I've designed a learning path to help me upskill to build pipelines on nextflow. I believe nextflow programming is a valuable skill set for a bioinformatician, especially one working/pursuing research in genomics. Since I had a tough time collating resources myself, I'm sharing the learning path here. Hopefully, it benefits someone else who's lost in the sea of information that all the well-meaning experts on the bioinformatics threads provide.

Nextflow for Bioinformatics: Comprehensive Study Program

Total Duration: 28 weeks (approximately 7 months)

Total Study Hours: 1,120 hours

1. Milestone: Foundations (160 hours)

Program 1: Introduction to Programming (80 hours)

• Book: "Python for Biologists" by Martin Jones

  https://pythonforbiologists.com/

• Online Course: Codecademy's "Learn Python 3"

  https://www.codecademy.com/learn/learn-python-3

• Video Series: MIT OpenCourseWare's "Introduction to Computer Science and Programming in Python"

  https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/

Program 2: Linux Basics and Command Line (40 hours)

• Book: "The Linux Command Line" by William Shotts

  https://linuxcommand.org/tlcl.php

• Online Course: edX's "Introduction to Linux"

  https://www.edx.org/course/introduction-to-linux

• Tutorial: Linux Journey

  https://linuxjourney.com/

Program 3: Introduction to Bioinformatics (40 hours)

• Book: "Bioinformatics Data Skills" by Vince Buffalo

  https://www.oreilly.com/library/view/bioinformatics-data-skills/9781449367480/

• Online Course: Coursera's "Introduction to Bioinformatics" by UC San Diego

  https://www.coursera.org/learn/bioinformatics

• Resource: NCBI Handbook

  https://www.ncbi.nlm.nih.gov/books/NBK143764/

2. Milestone: Nextflow Basics (160 hours)

Program 4: Nextflow Fundamentals (80 hours)

• Official Nextflow Documentation

  https://www.nextflow.io/docs/latest/index.html

• Nextflow Training

  https://training.nextflow.io/

• Video: "Getting Started with Nextflow" by Paolo Di Tommaso

  https://www.youtube.com/watch?v=8_i8Tn335X0

Program 5: Nextflow Scripting (80 hours)

• Nextflow Patterns

  https://github.com/nextflow-io/patterns

• Nextflow Examples

  https://github.com/nextflow-io/examples

• Blog: "Nextflow Concepts for Beginners" by Zhuoqing Fang

  https://zhuoqingfang.medium.com/nextflow-concepts-for-beginners-b86ce7c2b06d

3. Milestone: Intermediate Nextflow (240 hours)

Program 6: Advanced Nextflow Concepts (120 hours)

• Nextflow Configuration Documentation

  https://www.nextflow.io/docs/latest/config.html

• Nextflow Error Handling Guide

  https://www.nextflow.io/docs/latest/tracing.html

• Blog: "Nextflow Workflow Patterns" by Phil Ewels

  https://www.nextflow.io/blog/2019/workflow-patterns-in-nextflow.html

Program 7: Nextflow DSL2 (80 hours)

• Nextflow DSL2 Documentation

  https://www.nextflow.io/docs/latest/dsl2.html

• Workshop: "Nextflow DSL2 Workshop" by Seqera Labs

  https://github.com/seqeralabs/nextflow-workshop

• Video: "Introduction to Nextflow DSL2" by Paolo Di Tommaso

  https://www.youtube.com/watch?v=rjkWHehhTXg

Program 8: Version Control with Git (40 hours)

• Book: "Pro Git" by Scott Chacon and Ben Straub

  https://git-scm.com/book/en/v2

• Online Course: Codecademy's "Learn Git"

  https://www.codecademy.com/learn/learn-git

• Interactive Tutorial: Learn Git Branching

  https://learngitbranching.js.org/

4. Milestone: Bioinformatics Applications (320 hours)

Program 9: NGS Data Analysis with Nextflow (160 hours)

• Book: "Bioinformatics Data Skills" by Vince Buffalo (chapters on NGS analysis)

  https://www.oreilly.com/library/view/bioinformatics-data-skills/9781449367480/

• Online Course: Galaxy Training Network's NGS tutorials

  https://training.galaxyproject.org/training-material/topics/sequence-analysis/

• Nextflow Pipelines: nf-core

  https://nf-co.re/

Program 10: Containerization and Reproducibility (80 hours)

• Docker Documentation

  https://docs.docker.com/

• Online Course: edX's "Introduction to Containers w/ Docker, Kubernetes & OpenShift"

  https://www.edx.org/course/introduction-to-containers-w-docker-kubernetes-openshift

• Nextflow Container Documentation

  https://www.nextflow.io/docs/latest/container.html

Program 11: High-Performance Computing with Nextflow (80 hours)

• Nextflow Executor Documentation

  https://www.nextflow.io/docs/latest/executor.html

• Online Course: FutureLearn's "High-Performance Computing in the Cloud"

  https://www.futurelearn.com/courses/high-performance-computing-cloud

• Tutorial: "Running Nextflow on AWS Batch"

  https://www.nextflow.io/docs/latest/awscloud.html

5. Milestone: Advanced Topics and Projects (240 hours)

Program 12: Nextflow Pipelines and nf-core (80 hours)

• nf-core Documentation

  https://nf-co.re/usage/introduction

• nf-core Tutorials

  https://nf-co.re/usage/tutorials

• Video: "Introduction to nf-core" by Phil Ewels

  https://www.youtube.com/watch?v=gUM9acK25tQ

Program 13: Custom Pipeline Development (120 hours)

• Nextflow Best Practices

  https://www.nextflow.io/docs/latest/best-practices.html

• Case Studies: Nextflow Community Pipelines

  https://github.com/nextflow-io/awesome-nextflow

• Workshop: "Building Reproducible Workflows with Nextflow and nf-core"

  https://github.com/nf-core/nf-core-workshops

Program 14: Best Practices and Optimization (40 hours)

• Nextflow Performance Tuning Guide

  https://www.nextflow.io/docs/latest/perftuning.html

• Blog: "Nextflow Optimization Tips" by Evan Floden

  https://www.nextflow.io/blog/2019/optimize-nextflow-pipelines.html

• Webinar: "Nextflow Optimization and Best Practices" by Seqera Labs

  https://www.youtube.com/watch?v=IjvjlxHVMAo

Note: This program is designed for intensive study, assuming approximately 40 hours per week. Adjust the pace as needed based on your circumstances and learning speed.

PS: I've just started with this and am on Milestone 1 of this journey. If anyone decides to follow this learning path, I'd love to hear about your progress and if this plan benefitted you. For those in the know, if any of these resources are outdated or not recommended, I'm open to critique and will update the plan on the thread.

Thanks for reading if you got this far!

Hi am new to Rstudio and can’t figure out how to solve this error

this is the code so far:

install.packages("skimr") library("skimr") install.packages("openintro") library("openintro") install.packages("vctrs") skim(classdata) View(classdata.(1)) install.packages("ggplot2") library("ggplot2") install.packages library("tidyverse")

ggplot(classdata.(1), aes(x = lecture, y = m1, fill = lecture) geom_boxplot()

The error message:

Error: unexpected symbol in: "ggplot(classdata.(1), aes(x = lecture, y = m1) geom_boxplot"

the data set: class data from openintro

I wish to individually pursue a bioinformatics project, but I'm not sure where exactly to start, or what to look for. I've had suggestions to work on projects using R and Python, but again, I don't know what kind of project to take up, and how to choose the right subject - I just need an outline of what avenues can be pursued in this field. Also, I want the project to be big enough to keep me engaged for 3 months or more.

Hii. I'm in urgent need of help for my analysis. I'm still new to the field and do not have experience in coding or R and am therefore using online tools for my analysis such as iDEP, ShinyGO and GEO2R. If there is anyone who can help, please DM. I would greatly appreciate your help. 🥺 I can explain you the analysis I am doing and the context too

Hi, people can we please comment all the resources that one can/should use if they're entering the field of bioinformatics or must know about going ahead in the field?! Thank you very much.

So I've asked before what distro I should go with to start off with Linux, which I will primarily use for my Bioinformatics work (and later transition to as a personal-use OS), and I ended up with a whole array of options.

Now I'm stuck between Ubuntu (LTS, Pop OS), Fedora or Debian. I guess each has its own perks (but also downs).

I also learnt about containerization and how it could help resolve stability related issues.

I want to know if dual booting 2 different distros (with contrasting features) would be helpful to rid this dilemma, and if so, which 2 should I choose?