Pratik @pratiknsingh

“Be curious, not judgmental, and above all, be kind” Joined September 2015

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105
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262
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361

Susan Kilgas @SusanKilgas

3 days ago

Excited to share our new paper from Sara J. Buhrlage lab & @ChowdhuryLab! We designed CAS-010, a selective, low nanomolar USP28 inhibitor that reduces p53 transcriptional activity, mimics p53 pathway loss & disrupts 53BP1-USP28 binding, offering new insights into USP28 function.

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Manolis Kellis @manoliskellis

a week ago

MIT Course announcement: Machine Learning for Computational Biology #MLCB25 Fall'24 Lecture Videos: tinyurl.com/MLCBlectures Fall'24 Lecture Notes: tinyurl.com/MLCB24notes (a) Genomes: Statistical genomics, gene regulation, genome language models, chromatin structure, 3D genome…

Manolis Kellis @manoliskellis

7 years ago

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Balaji @Bajji

a week ago

Excited to share our new study in 𝘾𝙖𝙣𝙘𝙚𝙧 𝙍𝙚𝙨𝙚𝙖𝙧𝙘𝙝! We focus on PROX1 as a key driver of neuroendocrine #ProstateCancer and highlight its potential as a therapeutic target. Huge thanks to @mishabeltran for her mentorship! bit.ly/3HRIvAU @PCF_Science @CDMRP

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Cell Reports @CellReports

2 weeks ago

Integrative genomic identification of therapeutic targets for pancreatic cancer dlvr.it/TMdKH2

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ShorterLab @ShorterLab

2 weeks ago

CRISPR screening by AAV episome-sequencing (CrAAVe-seq): a scalable cell-type-specific in vivo platform uncovers neuronal essential genes: nature.com/articles/s4159…

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Prof. Nikolai Slavov @slavov_n

2 weeks ago

If you measure and interpret RNA levels in single cells, read this: "Our results suggest that instantaneous mRNA abundance of canonical markers is tenuously linked to the chondrogenic phenotype at the single-cell level." 1/2

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Nature Reviews Drug Discovery @NatRevDrugDisc

2 weeks ago

For readers interested in the growing therapeutic applications for GLP-1 based drugs such as semaglutide and tirzepatide, here's a comprehensive review by @DanielJDrucker in the August issue nature.com/articles/s4157… rdcu.be/eBVB4

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Abhinav Adduri @abhinadduri

2 weeks ago

Learned a lot through this article on the intricacies of data generation and processing: arcinstitute.org/news/behind-th… It makes sense why there’s no foundation model for perturbations yet. So many variables like capture chemistry, UMI/cell, cells/perturbation, batch effects, technical…

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James Zou @james_y_zou

3 weeks ago

🌹Meet #ROSIE, our new AI that predicts spatial multi-protein expression straight from routine H&E images. Built on a large co‑staining dataset (>1k samples, 16M+ cells). It enables cell phenotyping & tissue structure insights w/o extra assays.

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Eric Topol @EricTopol

4 weeks ago

The brain is the master regulator of food intake and energy balance. A brilliant new @CellCellPress review, including the mechanism of GLP-1 drugs, by @ClemmensenC and colleagues, open-access cell.com/cell/fulltext/…

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Thomas Norman @thenormanlab

a month ago

Our paper is now out in final form at Nature Genetics! For those who missed the preprint, we used large-scale Perturb-seq targeting transcription factors to push primary fibroblasts into diverse transcriptional states, including those observed in cell atlas studies.

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Lilly Oncology Medical @LillyOncMed

2 months ago

CURRENTLY ENROLLING: A phase 2 clinical trial evaluating a CDK 4/6 inhibitor + temozolomide versus temozolomide monotherapy in children and young adults with newly diagnosed high-grade Glioma. HCPs - Find trial and enrollment info here: e.lilly/40ae2UB

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Prof. Nikolai Slavov @slavov_n

a month ago

How challenging is the prediction of transcriptional responses to CRISPR gene perturbations ? A simple model, just scaling RNA correlation vectors, results in accurate predictions for many perturbations. The model is intuitive & grounded in a simple approximation. 1/2

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Emmanuel Tsekleves @PhDtoProf

2 months ago

Step-by-step guide to write an introduction that convinces reviewers to accept and your audience to read more Are you writing brilliant research but getting rejected because your introductions put reviewers to sleep? This framework transforms rejection into acceptance 🧵

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Ming "Tommy" Tang @tangming2005

2 months ago

1/ Many genomics mistakes are hard to catch in the code. They’re in the data you never looked at. Genome browsers can change that. Here’s how.

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Ming "Tommy" Tang @tangming2005

2 months ago

🧵 1/ You think your study is groundbreaking? Wait until you learn how HeLa contamination skewed whole archives—misidentifications across thousands of papers.👇

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Daniel Gerlach @gerlach_d

6 years ago

Daniel Durocher (Lunenfeld-Tanenbaum Research Institute): Navigating gene-gene and drug-gene interaction landscapes underpinning the DNA damage response #Targets19

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Fabian Theis @fabian_theis

2 months ago

New OpenProblems paper out! 📝 Led by Malte Lücken with Smita Krishnaswamy, we present openproblems.bio – a community-driven platform benchmarking single-cell analysis methods. Excited about transparent, evolving best practices for the field! 🔗 nature.com/articles/s4158…

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Muhammad Hussain, MD @whosainastro

2 months ago

1/ Why is Ki-67 called Ki-67? And why am I attaching a photo of this beautiful city to the tweet? If you work in pathology or oncology, you’ve likely come across Ki-67 many times. But where does the name come from? A short 🧵 on the origins, function, and significance of Ki-67.…

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Charlie Wright @biowright

a year ago

Great time at #AACR24 discussing use of CRISPR anchor screens to nominate drug combinations, and how to screen those combinations in ultrahigh-throughput. Two posters in the same session at the same time though 🫠 #AACR2024