@akshay_pachaar In addition to this, there are other nice data analytics and visualization tools that leverage Gen AI
1. Dataline (https://t.co/YOXua3v2DE)
2. Julius Ai (https://t.co/5MZsgc49Q9)
I'm making an open offer to any compbio grad students/postdocs who are aiming for faculty positions. If you have strong impactful research but no glam pubs & need someone to advocate for you, please get in touch. I promise u, I & a bunch of other faculty will strongly support u.
@anshulkundaje@thabangh@ZhipingWeng@UMassChan@IMPvienna @WUSTL If you're interested in my work, or the general genomics + ML field, and looking for a position starting in ~2025, please reach out! I'll be looking to hire grad students, post-docs, and staff scientists.
Any self-identified #male researchers out there doing #DataScience in #women'sHealth? I am looking for speakers at the session that I will chair at DahShu Data Science Symposium, May 16-18th in Michigan State University. Please self-recommend or nominate, or RT. Thanks!
AI tools that can help you chat with your data through the most common programming languages.
1. Vanna https://t.co/SRdat0XaEj
2. PandasAI: https://t.co/548XEn9CuI
3. RTutor: https://t.co/mtIg57eUFk
These tools are open source and make data analysis conversational.
Vanna is a Python-based AI that writes SQL queries for you. It is free and can be used with its own API (free) to train and ask questions. Very easy to install, train your own LLM, and ask questions. Also, have UI. Very impressed with the simplicity https://t.co/SRdat0XaEj
@tangming2005 You have to be precise with your timelines when working in a company. A rule of thumb would be to look at how much time it took for a similar analysis and add a week. We have a KPI ("NGS analysis turnaround") that we have been tracking which is helping us to answer that question.
@strnr Thanks for sharing this list. All of them look super interesting. I bookmarked them and started reading the RNA-Seq paper already.
How did you manage to read them all in 2 weeks? It's a lot
2023 has been a special year: we released https://t.co/7b5V9AcmiH. Since then it grew to more than 500 repos with #bioinformatics#training material.
Kudos to all the contributors! Especially to @P_Palagi and @choup.
Below are some top 3s of topics, organizations, and repos.
@IgorUlitsky I like the idea of creating a "papers" Slack channel. We also do once-a-month JC and we rotate within and whoever is presenting will send a relevant paper to the group 2 weeks before. We have "Key Takeaways" and "Discussion" slides in addition to figures and background slides.
@MatildeConcilio @MannaLiberato I agree with you as well. I got my first Postdoc that way. Of course, I had to interview before I got accepted but everything started with that one email expressing my interest. Never hurts to send an email expressing your interest in working in that lab.
I’m looking for a postdoc who would like to work primarily in the wet lab while also learning a bit of computational protein design. Lots of exciting projects! Please reach out if interested!
Our latest work about eXplainable AI in genomics is published in PNAS: NeuronMotif is an algorithm to extract cis-regulatory grammar (motif combination, order, gap sizes) learned by convolutional neurons in a convolutional neural network (CNN).
https://t.co/IlW81RvWwt
All biology is computational biology.
data are omnipresent, learn computational skills and you will be unstoppable.
Take 5 mins to bookmark the following threads to guide your learning 👇🧵
https://t.co/YCaSUhUd2U