
Used to be an engineer, a statistician. Now a cancer biologist hooked up with @danliuorg for life.
Joined June 2015
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Jun Yin retweeted
The KRAS mutational spectrum and its clinical implications in pancreatic cancer dlvr.it/TD68gz
Jun Yin retweeted
Are there any good computational models for predicting protein level based on RNA expression, especially for cell surface proteins (e.g. PDL1) or proteins with post-translational modification? A good model could improve disease biomarkers and find new therapeutic opportunities.
Jun Yin retweeted
"Compelling evidence for the role of carboxylic acid in guiding the mosquito's preference toward specific people"
cell.com/cell/fulltext/S0092… @CellCellPress
Jun Yin retweeted
Join us @theNCI #Computational #ImmunoOncology #virtual workshop, Monday 9/19!! 🤩
Stellar lineup of speakers discussing #multimodal integration, #AI, #deeplearning, and medical discoveries to inform #therapeutic development using #IO #data!
bit.ly/3DteGlx @sitcancer
Jun Yin retweeted
Representing my friend and ⭐️ fellow @AsaadTrabolsi with his great work on the tumor microenvironment of HRAS mutated #NSCLC at #ESMO22
@GlopesMd @Latinamd @HemOncFellows @SylvesterCancer @carisls – at Paris, France
Jun Yin retweeted
A large-scale, whole-genome analysis in Science of over 12,000 cancers reveals previously unreported mutational signatures, including tumor-specific rare signatures. The findings could potentially help enhance personalized cancer treatments and diagnoses. fcld.ly/1cugdml
Jun Yin retweeted
Four reasons why I think authorship on academic papers should be more like movie credits:
Jun Yin retweeted
Don’t miss @jennifermarksmd’s presentation on MET exon 14 skipping mutations in the mini-oral session on molecular profiling. These mutations are variable and occur in squamous and non-squamous NSCLC. #WCLC22
Jun Yin retweeted
New blog post: Add labels to circular heatmap
jokergoo.github.io/2022/07/2…
Jun Yin retweeted
And the deep learning vs conventional machine learning for tabular data continues!
A new paper looks at 45 mid-sized datasets (10k examples) and finds that tree-based models (XGBoost & random forests) still outperform deep neural networks on tabular datasets. [1/6]
Jun Yin retweeted
1/ We previously generated a 1M cell scRNA-seq dataset with 24 Type1 Diabetes/Control PBMC samples. Now Daniel Diaz, one of our Bioinformatics Application Scientists, has built a tutorial showing how you can easily analyze this dataset using existing single cell tools.
Jun Yin retweeted
Our special issue on #AI for molecular biology we edited for @JMolBiol is out!
Check out great papers on AI for #proteinfolding, #microbiome, #3Dgenome and more!
Issue sciencedirect.com/journal/jo…?
Our editorial sciencedirect.com/science/ar…
Ruishan's RNA-ODE paper sciencedirect.com/science/ar…
Jun Yin retweeted
Going to Paris for the first time!!! 🇫🇷🥳
Excited to present our abstract on characteristics/outcomes in HRAS-mutated urothelial #bladdercancer at #ESMO22
Many thanks to my amazing mentors! @JaimeMerchan10 @Latinamd @GlopesMd @AsaadTrabolsi @SamuelKareffMD @slowwalker919 – at Miami, FL
Jun Yin retweeted
12 Best #DataScience Courses for Working Professionals in 2022 — compiled by @tut_ml
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#BigData #DataScientists #AI #MachineLearning #Python #Coding #100DaysOfCode
mltut.com/best-data-science-…
Oh wow superstar!!!!! Awesome to have you as a collaborator
Thanks @Keira_i3Health for recording my first ever podcast! Still have a ways to go to get to the likes of @NarjustFlorezMD @StephenVLiu @JackWestMD @chadinabhan 😂
Looking forward to the next one @i3health 📻 💻📱
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Jun Yin retweeted
Super excited to share our new @NatureMedicine paper on #precisioncancer!
We use tumor genomes + EHR of >40K cancer patients to identify 458 mutations that predict how a patient responds to specific cancer drugs
Paper rdcu.be/cQJvZ
Great collab w/ @Roche @genentech 🧵
Jun Yin retweeted
People with similar body odors are more likely to hit it off and become friends, according to a new study in @ScienceAdvances. fcld.ly/fmiucsu
Jun Yin retweeted
dair-ai/ML-Notebooks: A series of code examples for all sorts of machine learning tasks and applications. github.com/dair-ai/ML-Notebo… #MachineLearning






























