Show me your neighbors and I'll tell you who you are - the single cell transcriptomics edition. Statistician, postdoc @broadinstitute, @MIA_at_Broad, @TheHDSR
Cambridge, Massachusetts
Joined September 2020
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Aleks Goeva retweeted
We can often reconstruct a certain layer of information from single-cell data, like their spatial configuration or trajectory, but what can we learn when we peel that layer off? What else is encoded? SiFT is out @NatureComms, Led by @zoe_piran
nature.com/articles/s41467-0…
@HebrewU
Interested in uncovering biological processes in single-cell data? Check out SiFT, featured in @NatureComms. SiFT peels off layers of known variability and allows studying previously unexplored bio signals. Try it yourself: sift-sc.readthedocs.io. w/ @mor_nitzan
Artwork: Reo F.
Aleks Goeva retweeted
Interested in uncovering biological processes in single-cell data? Check out SiFT, featured in @NatureComms. SiFT peels off layers of known variability and allows studying previously unexplored bio signals. Try it yourself: sift-sc.readthedocs.io. w/ @mor_nitzan
Artwork: Reo F.
Cells simultaneously encode multiple signals, some overshadowed. @mor_nitzan @zoe_piran introduce SiFT (Signal FilTering), a kernel-based projection method, revealing underlying biological processes in single-cell data. @NatureComms #BiotechNatureComms
nature.com/articles/s41467-0…
Aleks Goeva retweeted
Consider submitting your work to the Machine Learning for Genomics Explorations (MLGenX) workshop at @iclr_conf ! Join us to unite the worlds of #MachineLearning & #Genomics 🧬
⏰Submission deadline: February 4, 2024 (AOE).
📢🚨 Excited to announce the Machine Learning for Genomics Explorations (MLGenX) workshop at @iclr_conf 2024.
⏰ Submission deadline: February 4, 2024 (AOE).
🔗 Call for papers: mlgenx.github.io
🗓️ Date: May 11, 2024.
Aleks Goeva retweeted
MIA Spring ‘23 Speaker Series
⏰ April 5, 9AM EST
💬 Lucy Colwell, Benjamin Sanchez-Lengeling @beangoben
💡Primer: Intro to machine learning for molecules
💡Seminar: ML to predict protein function from sequence ...
📬 Join our mailing list to get the talk link!
#BroadMIA
Aleks Goeva retweeted
Join my group at Genentech and follow your passion for single-cell tumor dynamics!
Both experimental and computational positions available.
Apply below:
Cancer Single-Cell Genomics: lnkd.in/eR2eCqPd
Computational Biology: lnkd.in/e7TeHsXg
So excited for @oana__ursu and @_bunnech’s talks this Wednesday at #BroadMIA! Tune in at 9AM EST to learn about computational approaches to study single-cell state transitions and responses to perturbation!
📢 Nov 16
⏰ 9AM EST
💬 Oana Ursu @oana__ursu
💡 Primer: Analytical challenges and opportunities for studying cell state transitions at single cell level
⏰ 10AM EST
💬 Charlotte Bunne @_bunnech
💡 Neural Optimal Transport for Inferring Single-Cell Responses to Perturbations
The submission deadline for @lmrl_bio at #NeurIPS2022 is this Friday, Sept 30th! Submit your 1 to 4-page abstract at openreview.net/group?id=Neur…! More info lmrl.org/. RT appreciated!
Organizing committee: @adjiboussodieng @AleksGoeva @anshulkundaje @chang_c_liu @deboramarks @eboyden3 @EliWeinstein6 @lizbwood @lorin_crawford @mor_nitzan @RBoiarsky @_romain_lopez_ @thouis @stephenrra @ta_broderick @WouterBoomsmaDK @yixinwang_
Aleks Goeva retweeted
Looking forward to my @MIA_at_Broad talk tomorrow, and honoured to be featured alongside @drklly . Thanks for hosting, @AleksGoeva !
📢 MIA Fall ‘22 Speaker Series
⏰ Sept 21, 9AM EST
💬 David Kelley @drklly
💡 Primer: Gene expression prediction from DNA sequences
⏰ Sept 21, 10AM EST
💬 Carl de Boer @CarldeBoerPhD
💡 Using deep learning regulatory models and random DNA for evolutionary inference
#BroadMIA
So excited for this Wednesday’s #BroadMIA when @drklly and @CarldeBoerPhD will tells us what’s new in using #DeepLearning to understand #GeneRegulation!
📢 MIA Fall ‘22 Speaker Series
⏰ Sept 21, 9AM EST
💬 David Kelley @drklly
💡 Primer: Gene expression prediction from DNA sequences
⏰ Sept 21, 10AM EST
💬 Carl de Boer @CarldeBoerPhD
💡 Using deep learning regulatory models and random DNA for evolutionary inference
#BroadMIA
Aleks Goeva retweeted
Just one among many reasons @lmrl_bio is proudly virtual at @NeurIPSConf this year. Submit your abstract by Sep 30, 2022: lmrl.org/submit
I made an accessibility map of #Neurips2022. The country is marked in red if its resident can not get appointment in time from getting accepted to the conference (76 days).
Aleks Goeva retweeted
Science is unbearable if you hold off on celebrating until the publication of a big paper. The more we enjoy the process, the happier we are..
Celebrate the interesting group meeting, the preparation of a new presentation, the new technique, & the progress our friends are making.
Tune in this morning for Martin Jankowiak’s #BroadMIA talks on Bayesian Variable Selection with exciting #biology applications! Starting in 10 min!
📢 MIA Fall ‘22 Speaker Series
⏰ Sept 14, 9AM EST
💬 Martin Jankowiak
💡Primer: An Introduction to Bayesian Variable Selection
💡Seminar: Applications of Bayesian Variable Selection to Bioinformatics
📬 Join our mailing list to get the talk link!
#BroadMIA
Get ready for the Fall #BroadMIA lineup of #pedagogical #CuttingEdge talks at the interface of #MachineLearning and #biology 👩🔬🧬💻🧫👩💻
Aleks Goeva retweeted
New from @TheHDSR Early Career Board: @AleksGoeva, @atrisovic, @mission_science, & I made a zine about @JessicaHullman and @StatModeling's paper "Designing for interactive exploratory data analysis requires theory of graphical inference" Thanks @sarahmirk for the zine tutorial!
Aleks Goeva retweeted
A Gentle Introduction to Graph Neural Networks by @beangoben, @emilyrreif, @adamrpearce, and Alex Wiltschko.
distill.pub/2021/gnn-intro/
Aleks Goeva retweeted
Csiszar f-divergences (KL, TV, Hellinger, Chi2, etc) are all closely related and define similar topologies. Wasserstein distance in contrast requires upper/lower bounds on the spacing between the points. Nice review by Gibbs and Su. en.wikipedia.org/wiki/F-dive… math.hmc.edu/~su/papers.dir/…
Aleks Goeva retweeted
Finally, we added new example datasets! You can access SeqFISH, MERFISH, Slide-seqV2, Visium, Mibi-tof, 4i, IMC datasets through the Squidpy API to try out all the new functions!
squidpy.readthedocs.io/en/st…
Thanks to @macosko @AleksGoeva for providing pre-processed Slide-seqV2 data!
Aleks Goeva retweeted
We worked for years to profile human dopamine neurons at scale; @abdul_squared cracked it. @tkam80 revealed the full diversity of DA neurons in the substantia nigra, and their relative vulnerabilities to degeneration in Parkinson's disease.
biorxiv.org/content/10.1101/…
Aleks Goeva retweeted
The Early Career Board of @TheHDSR is a most creative board I have ever worked with. My last invitation to @AleksGoeva : “Feel free to be innovative re the format, and surprise me! :-)”. They did, in a delicious way! Wondering what’s cooking next…(no pressure, Aleks & all :-))
After taking @UCBerkeley's Data8: The Foundations of #DataScience, what connector courses do you dream of taking? Sip your favorite beverage and enjoy the recipes @sastoudt , @atrisovic, Peyton Jones, and I compiled for @TheHDSR hdsr.mitpress.mit.edu/pub/4i…
