Sign in

Gherman Novakovsky

@gnovakovsky.bsky.social
174 followers 141 following 20 posts

PhD, Illumina AI lab

PostsRepliesMedia
Reposted by Gherman Novakovsky
Dariia Mykhailyshyna @dariia.bsky.social · 14/11/2025
❗️Our next workshop will be on Dec 11 6 pm CET titled A Gentle Introduction to Mathematical Simulation in R by @damiepak.bsky.social Register or sponsor a student by donating to support Ukraine! Details: bit.ly/3wBeY4S Please share! #AcademicSky #EconSky #RStats
12512
Reposted by Gherman Novakovsky
Wyeth Wasserman @wywywa.bsky.social · 22/07/2025
I'm hiring a Bioinformatics Research Associate for the Silent Genomes Project. PhD required, restricted to Canadians, work must be performed in British Columbia. Great for those who love pipelines, whole genome data and work with a social purpose. ubc.wd10.myworkdayjobs.com/ubcfacultyjo...
ubc.wd10.myworkdayjobs.com
Research Associate
Academic Job Category Faculty Non Bargaining Job Title Research Associate Department Wasserman Laboratory | Department of Medical Genetics | Faculty of Medicine (Wyeth Wasserman) Posting End Date Augu...
066
Reposted by Gherman Novakovsky
Anshul Kundaje @anshulkundaje.bsky.social · 19/06/2025
@saramostafavi.bsky.social (@Genentech) & I (@Stanford) r excited to announce co-advised postdoc positions for candidates with deep expertise in ML for bio (especially sequence to function models, causal perturbational models & single cell models). See details below. Pls RT 1/
15439
Gherman Novakovsky @gnovakovsky.bsky.social · 30/05/2025
Excited to share my first contribution here at Illumina! We developed PromoterAI, a deep neural network that accurately identifies non-coding promoter variants that disrupt gene expression.🧵 (1/)
15921
Reposted by Gherman Novakovsky
Stein Aerts @steinaerts.bsky.social · 16/05/2025
Two massive glioblastoma papers, datasets, trajectories, insights, and.. a very cool new method for GRN inference - scDORI -from @steglelab.bsky.social @oliverstegle.bsky.social @bayraktarlab.bsky.social & Moritz Mall www.biorxiv.org/content/10.1... www.biorxiv.org/content/10.1...
biorxiv.org
Decoding Plasticity Regulators and Transition Trajectories in Glioblastoma with Single-cell Multiomics
Glioblastoma (GB) is one of the most lethal human cancers, marked by profound intratumoral heterogeneity and near-universal treatment resistance. Cellular plasticity, the capacity of cancer cells to t...
13816
Reposted by Gherman Novakovsky
Manu Saraswat @manusaraswat.bsky.social · 16/05/2025
🧠 Excited to share my main PhD project! We mapped the regulatory rules governing Glioblastoma plasticity using single-cell multi-omics and deep learning. This work is part of a two-paper series with @bayraktarlab.bsky.social @oliverstegle.bsky.social and @moritzmall.bsky.social, Preprint at end🧵👇
17930
Reposted by Gherman Novakovsky
Haky Im @hakyim.bsky.social · 14/05/2025
Check out our scPrediXcan paper www.cell.com/cell-genomic... Led by the talented @Charles_Zhou12 and supervised by @MengjieChen6 and me, with thanks to many contributors. scPrediXcan integrates deep learning and single cell expression data into a powerful cell type specific TWAS framework.
cell.com
scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework
Zhou et al. introduce scPrediXcan, a novel transcriptome-wide association study framework that integrates the deep learning-based model ctPred for cell-type-specific expression prediction. Applied to ...
0156
Reposted by Gherman Novakovsky
claricehongky.bsky.social @claricehongky.bsky.social · 23/04/2025
So excited to see Yawei's manuscript on long-range MPRAs out! Some really great insights into distal enhancer regulation 🙂
1154
Reposted by Gherman Novakovsky
Milot Mirdita @milot.bsky.social · 24/04/2025
Day 1 of #RECOMB2025​-SEQ starts with @rayanchikhi.bsky.social and an introduction to Logan, a planetary-scale effort to assemble everything. Currently cataloguing about 700k virus species! 📄 www.biorxiv.org/content/10.1...
1204
Reposted by Gherman Novakovsky
Jesse Engreitz @jengreitz.bsky.social · 17/04/2025
Our latest work now online in Cell: Rewriting regulatory DNA to dissect and reprogram gene expression Our new method (Variant-EFFECTS) uses high-throughput prime editing + flow sorting + sequencing to precisely measure effects of noncoding variants on gene expression Thread 👇
111728
Reposted by Gherman Novakovsky
Anya Korsakova @anyakors.bsky.social · 16/04/2025
⚡️ Our latest preprint is on bioRxiv! Shift augmentation improves DNA convolutional neural network indel effect predictions www.biorxiv.org/content/10.1...
biorxiv.org
Shift augmentation improves DNA convolutional neural network indel effect predictions
Determining genetic variant effects on molecular phenotypes like gene expression is a task of paramount importance to medical genetics. DNA convolutional neural networks (CNNs) attain state-of-the-art...
2135
Reposted by Gherman Novakovsky
Niklas Kempynck @niklaskemp.bsky.social · 03/04/2025
We released our preprint on the CREsted package. CREsted allows for complete modeling of cell type-specific enhancer codes from scATAC-seq data. We demonstrate CREsted’s robust functionality in various species and tissues, and in vivo validate our findings: www.biorxiv.org/content/10.1...
17538
Reposted by Gherman Novakovsky
Wyeth Wasserman @wywywa.bsky.social · 27/02/2025
Bioinformatics Job Opportunity Research Associate / Staff Scientist Vancouver Canada Join the Silent Genomes Project to provide an outstanding genetic variation database for Indigenous peoples of Canada to improve rare disease diagnosis tinyurl.com/bm4ptux3 Priority to Canadians Please repost
tinyurl.com
Research Associate
Academic Job Category Faculty Non Bargaining Job Title Research Associate Department Wasserman Laboratory | Department of Medical Genetics | Faculty of Medicine (Wyeth Wasserman) Posting End Date Febr...
02830
Reposted by Gherman Novakovsky
Vikram Agarwal @vagar.bsky.social · 15/01/2025
Super excited to announce our latest work. On a personal note, it's not an exaggeration to say that blood, sweat, and tears got us to the finish line on this: working w/ an outstanding global team of scientists in Germany, Japan, Russia, and USA responding in >100 pages of complex reviewer comments.
nature.com
Massively parallel characterization of transcriptional regulatory elements - Nature
Lentivirus-based reporter assays for 680,000 regulatory sequences from three cell lines coupled to machine-learning models lead to insights into the grammar of cis-regulatory elements.
23610
Reposted by Gherman Novakovsky
Nadav Ahituv @nadavahituv.bsky.social · 15/01/2025
Massively parallel reporter assays (MPRAs) testing >680,000 sequences combined with machine learning to improve regulatory element & variant effect prediction. Amazing work by @vagar.bsky.social, Fumitaka Inoue, @jshendure.bsky.social and many others as part of ENCODE. www.nature.com/articles/s41...
nature.com
Massively parallel characterization of transcriptional regulatory elements - Nature
Lentivirus-based reporter assays for 680,000 regulatory sequences from three cell lines coupled to machine-learning models lead to insights into the grammar of cis-regulatory elements.
19540
Reposted by Gherman Novakovsky
Vikram Agarwal @vagar.bsky.social · 09/01/2025
Super excited to announce our latest flagship model Borzoi: major props to Johannes & David Kelley et al for advancing it. It's been a long journey from our prior Enformer model into this one. A few innovations: i) longer DNA context, ii) adaptation to predict RNA-seq abundance and splice isoforms,
nature.com
Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation - Nature Genetics
Borzoi adapts the Enformer sequence-to-expression model to directly predict RNA-seq coverage, enabling the in-silico analysis of variant effects across multiple layers of gene regulation.
27127
Reposted by Gherman Novakovsky
Anshul Kundaje @anshulkundaje.bsky.social · 09/01/2025
Our original biorxiv submission of the ChromBPNet preprint had issues with supp. methods & file links not working (even though we they were uploaded). This updated version has fixed those issues. Everything shud be available now. Thanks for your patience. www.biorxiv.org/content/10.1...
biorxiv.org
ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants
Despite extensive mapping of cis-regulatory elements (cREs) across cellular contexts with chromatin accessibility assays, the sequence syntax and genetic variants that regulate transcription factor (T...
1375
Reposted by Gherman Novakovsky
Hani Goodarzi @genophoria.bsky.social · 02/01/2025
The first preprint of 2025! Together with Matvei, @halfacrocodile.bsky.social, & our amazing team, we are excited to share PARADE: an AI framework for designing mRNA UTRs with enhanced cell-type specificity & stability. www.biorxiv.org/content/10.1...
biorxiv.org
A generative framework for enhanced cell-type specificity in rationally designed mRNAs
mRNA delivery offers new opportunities for disease treatment by directing cells to produce therapeutic proteins. However, designing highly stable mRNAs with programmable cell type-specificity remains ...
18138
Reposted by Gherman Novakovsky
Sung Kim @sungkim.bsky.social · 23/12/2024
How to Accurately Time CUDA Kernels in Pytorch In a world of increasingly costly machine learning model deployments, ensuring accurate GPU operation timing is key to resource optimization. In this blog post, we explore best practices to achieve this in PyTorch. www.speechmatics.com/company/arti...
speechmatics.com
How to Accurately Time CUDA Kernels in Pytorch
In a world of increasingly costly machine learning model deployments, ensuring accurate GPU operation timing is key to resource optimization. Read more!
0214
Reposted by Gherman Novakovsky
Sarah Marzi @sj-marzi.bsky.social · 11/12/2024
So excited that our work on predicting gene expression from histone modifications using deep learning is out in NAR today. Brilliant to work with lead author @al-murphy.bsky.social and collaborators Aydan Askarova, @borislenhard.bsky.social and Nathan Skene 🧬⭐️🙏 academic.oup.com/nar/advance-...
academic.oup.com
Predicting gene expression from histone marks using chromatin deep learning models depends on histone mark function, regulatory distance and cellular states
Abstract. To understand the complex relationship between histone mark activity and gene expression, recent advances have used in silico predictions based o
37029
Reposted by Gherman Novakovsky
Austin Wang @austintwang.bsky.social · 11/12/2024
(1/10) Excited to announce our latest work! @arpita-s.bsky.social, @amanpatel100.bsky.social , and I will be presenting DART-Eval, a rigorous suite of evals for DNA Language Models on transcriptional regulatory DNA at #NeurIPS2024. Check it out! arxiv.org/abs/2412.05430
arxiv.org
DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA
Recent advances in self-supervised models for natural language, vision, and protein sequences have inspired the development of large genomic DNA language models (DNALMs). These models aim to learn gen...
17027
Reposted by Gherman Novakovsky
Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 19/09/2024
If you hate statistics like I do, then you'll love my free lectures. Putting science before statistics, 20 lectures from basics of inference & causal modeling to multilevel models & dynamic state space models. It's all free, made with love and sympathy. 🧪 #stats www.youtube.com/playlist?lis...
29852229
Reposted by Gherman Novakovsky
Axel Visel @axelvisel.bsky.social · 02/12/2024
Transcription and Chromatin Parts 1 and 2 by @jxhoffman.bsky.social Part 1: go.bsky.app/5zgpZfg Part 2: go.bsky.app/Q5sXc6E
174
Reposted by Gherman Novakovsky
Michael Kevin Spencer @aisupremacy.bsky.social · 02/12/2024
Computational Biology go.bsky.app/QVPoZXp
063
Reposted by Gherman Novakovsky
bioRxiv Genetics @biorxiv-genetic.bsky.social · 24/11/2024
Mapping enhancer-gene regulatory interactions from single-cell data www.biorxiv.org/content/10.1101/202…
biorxiv.org
Mapping enhancer-gene regulatory interactions from single-cell data https://www.biorxiv.org/content/10.1101/2024.11.23.624931v1
Mapping enhancers and their target genes in specific cell types is crucial for understanding gene re
03619