Discover and read the best of Twitter Threads about #ComputationalBiology
Most recents (13)
Why are biologists adopting #julialang #sciml? Performance, metaprogramming, and the development of new abstractions are improving software tools for #computationalbiology #systemsbiology #bioinformatics. Check out this new paper in Nature Methods!
nature.com/articles/s4159…
nature.com/articles/s4159…
In this we detail how #julialang's core compute model gives faster code, with a detailed calculation of the effects of the #python interpreter and kernel launching costs on simulation performance. It's pretty cool how one can pen and paper calculate the 100x expected difference. 
Julia's ecosystem has a complete set of tools for mathematical modeling (#sysbio), #bioinformatics, #machinelearning, and #datascience which we contextualize in the field of biology.
Sequencing data ====> Fancy figures in the paper.
The missing pieces? 👇 🧵
#rstats #computationalbiology
The missing pieces? 👇 🧵
#rstats #computationalbiology
1/ Quality control of the data. Any technical bias? sequencing depth difference?
2/ UNIX tools: alignment ---> quantification---> a table or a matrix
1/ If someone tells you that you can learn computation overnight, it is a lie. What I wish I had known 10 years ago with resource links👇🧵 #rstats #computationalbiology
2/ Spend time learning Linux commands. Fancy tools can become obsolete tomorrow, and Linux skills persist.
I started with this book linuxcommand.org/tlcl.php #unix
I started with this book linuxcommand.org/tlcl.php #unix
3/ Learn a language and learn it well. It does not matter if you pick R or python. If you can use it to solve your practical problems in the lab, that will be good. There is so much data wrangling to do, start with r4ds.had.co.nz #rstats
1. #Bioinformatics is the application of #computational techniques to the #analysis of #biological #data, such as #sequences, #structures, and #interactions, and is an essential field of modern biology and medicine.
2. #Bioinformatics has many exciting applications in various fields, such as #genetics, #genomics, #proteomics, and #metabolomics, that can provide new insights into the workings of living systems, and can help to advance science and society.
🧵🧵 THREAD: 9 tips for successful #bioinformatics #projects 🧵🧵
1. Start by defining the aim, scope, and objectives of your project, and by identifying the #biological and #computational questions you want to answer.
2. Identify the #data sources, types, and formats, that are relevant and available for your project, and evaluate their quality, quantity, and suitability.
🧵🧵 THREAD: #Bioinformatics and #AlphaFold 🧵🧵
1. #AlphaFold is a deep learning system developed by #DeepMind, to predict the 3D #structure of #proteins from their #aminoacid sequence.
2. #AlphaFold has been applied and tested extensively in the biennial #CASP (Critical Assessment of protein Structure Prediction) experiment, and has achieved state-of-the-art performance.
🧵🧵 THREAD: 10 reasons why #bioinformaticians should use #Nextflow 🧵🧵
1. #Nextflow is an open-source platform for #bioinformatics #pipelines and #workflows, designed to make them #scalable, #reproducible, and #portable.
2. #Nextflow allows #bioinformaticians to write their #pipelines and #workflows in a simple and expressive domain-specific language, called #Nextflow Script.
Vevo Therapeutics has officially launched out of stealth today with an oversubscribed and upsized $12M seed financing. We are so excited to reveal what we have been building behind the scenes! 🧵1/6
vevo.ai/#news
vevo.ai/#news
We're building the world’s largest in vivo, single-cell atlas of how drugs interact with patient cells. Combining this atlas with next-gen #AI, we aim to capture in vivo context of disease at the first step of discovery & better represent #PatientDiversity in drug response 2/6
What does this mean for patients? Better targets that would otherwise be missed, and drugs that are more likely to treat more patients. 3/6
1. #Cloud #computing allows #bioinformaticians to access and analyze large and complex #biological #data sets in a fast, scalable, and cost-effective manner.
2. The #cloud provides a flexible and dynamic #infrastructure that can be easily adjusted to the changing needs and demands of #bioinformatics projects.
On #biocompute news, $TSLA Tesla AI day gave some technical details on how they do their training and video labelling. It seems $NVDA Nvidia GPUs are the norm, with a 14,000 HPC heavily optimised on the software side. #pytorch #AVX2 #CUDA #SMT #smol #CUDNN
None of this is for the purpose of #Bioinformatics applications, rather here it's for Full Self-Driving software, but the technical details show some choices for high-throughput #AI training that one could compare to the #ComputationalBiology #ComputeAcceleration world.
More at bit.ly/biocompute
Bioinformatics vs Computational Biology
What is the difference? 🤔
#Bioinformatics #computationalbiology #Biology
🧵👇... (1/)
What is the difference? 🤔
#Bioinformatics #computationalbiology #Biology
🧵👇... (1/)
In many cases, the phrases “bioinformatics” and “computational biology” are used interchangeably, particularly in job descriptions or position titles.
Though the two fields are interrelated, bioinformatics and computational biology differ in the kinds of needs they address. (2/)
Though the two fields are interrelated, bioinformatics and computational biology differ in the kinds of needs they address. (2/)
Bioinformatics is a multidisciplinary field that combines biological knowledge with computer programming and big data.
It is the process by which biological problems posed by the study of biodata are interpreted and analyzed. (3/)
It is the process by which biological problems posed by the study of biodata are interpreted and analyzed. (3/)
1/ After a year of work, our paper on mRNA Degradation is finally out!
paper: arxiv.org/abs/2110.07531
code: github.com/eternagame/Kag…
paper: arxiv.org/abs/2110.07531
code: github.com/eternagame/Kag…
2/ A year ago I was approached with a unique and exciting opportunity: I was asked to help out with setting a Kaggle Open Vaccine competition, where the goal would be to come up with a Machine Learning model for the stability of RNA molecules.
3/ This is of a pressing importance for the development of the mRNA vaccines. The task seemed a bit daunting, since I have had no prior experience with RNA or Biophysics, but wanted to help out any way I could.
I am really thrilled to release #AutoSpill onto @biorxivpreprint. It is a novel method for applying compensation to #flowcytometry data, which reduces the error by ~100,000-fold. It is thanks to AutoSpill that we can push machines to their max colours
biorxiv.org/content/10.110…
biorxiv.org/content/10.110…
#AutoSpill is a beautiful example of what #maths can add to #immunology, led by the talented Dr Carlos Roca.
It has really open up my eyes to the potential of #computationalbiology, and is the reason why we have a new #datascience position available:
babrahaminstitute.livevacancies.co.uk/#/job/details/…
It has really open up my eyes to the potential of #computationalbiology, and is the reason why we have a new #datascience position available:
babrahaminstitute.livevacancies.co.uk/#/job/details/…
So how does #AutoSpill work? If you just want to compensate your data, simply upload your single colour controls to autospill.vib.be and then copy the spillover matrix to your #flowcytometry program of choice
@CarlyEWhyte can walk you through the whole process in <2'
@CarlyEWhyte can walk you through the whole process in <2'
