On Wed, July 13, Christopher Mancuso is giving a talk in BOSC #BOSC on "GenePlexus: A web server and Python package for gene discovery using network-based machine learning" Paper: doi.org/10.1093/nar/gk… Webserver: geneplexus.net Repo: github.com/krishnanlab/ge… #ISMB2022

We have 2 posters at #NetBio #ISMB2022 Christopher Mancuso | L-016 Jointly modeling networks from multiple species to improve gene classification Alex McKim | L-017 Module-based prediction improves network-based prioritization of genes associated w/ complex traits & diseases

We have 3 posters at TransMed COSI at ISMB/ECCB #ISMB2022 @kaylainbio | N-023 Age- and sex-specific gene signatures and networks Stephanie L Hickey | N-024 Chronic inflammation network signatures in complex diseases Kewalin Samart | Virtual Drug repurposing for infectious diseases w/ Janani Ravi

Two posters in MLCSB #ISMB2022 @NeutralYh | W-058 Cross-species transcriptome-based regression to discover model equivalents of human samples & genes. w/ @ingo_braasch Filip Jevtic | W-067 Determining the optimal embedding technique for mapping transcriptomes to ontologies

The Computational Biosciences PhD Program CU Anschutz Medical Campus is holding an Info Session on Fri, Oct. 21 for interested students to get to know the program! Plus, all registered attendees will receive an application fee waiver!! Please spread the word. graduateschool.cuanschutz.edu/events-and-res…

Automated NLP and ML approach to annotate samples to their tissue-of-origin by modeling unstructured metadata. Improved performance and scalability compared to MetaSRA ⁦Nature Communications⁩ ⁦Arjun Krishnan⁩ nature.com/articles/s4146…

The Krishnan Lab develops an approach combining natural language processing and machine learning to infer the source tissue of public genomics samples based on their plain text descriptions, making these samples easy to discover and reuse Arjun Krishnan go.nature.com/3UIi9lE

🎇 We're one of 20 finalists for the DataWorks! Prize for our work on: Removing metadata barriers to promote data reuse Methods that address unstructured & missing metadata that are barriers to discovering & reusing public omics data. Learn more & VOTE! herox.com/dataworks/roun…

A new software created by Arjun Krishnan, PhD, associate professor of biomedical informatics at CU Anschutz School of Medicine, and his team, annotates genomics samples based on unstructured sample text descriptions, making them easier for researchers to find and use.👇 nature.com/articles/s4146…

The Krishnan Lab develops an approach combining natural language processing and machine learning to infer the source tissue of public genomics samples based on their plain text descriptions, making these samples easy to discover and reuse Arjun Krishnan go.nature.com/3UIi9lE

This wk, @kaylainbio defended her brilliant PhD work on using #transcriptomes, #networks, & #machinelearning to probe age- & sex-specificity 🎉 Being the first grad student from Krishnan Lab, Kayla has set a v. high bar! Congratulations Dr. Johnson! We're very proud of you!!

Three University of Colorado Anschutz teams are DataWorks prize finalists! Learn more about Krishnan Lab, Monarch Initiative, and #NationalCovidCohortCollaborative's projects and vote for one here👇

The Ramanathan Lab is looking for a Research Tech to join us! We are a young and exciting group interested in how cells of diverse shapes and sizes form functional tissue. Please DM if you are interested in the position or want to know more! unmc.peopleadmin.com/postings/76294 Please RT!

🎉CONGRATS to the winners of the FASEB DataWorks! Prize🎉 🔁Grand Prize, Data Reuse: BrainChart — "Brain Charts for the Human Lifespan" 🤝Grand Prize, Data Sharing: N3C — "Democratizing Access to Clinical Data" Check out the winning projects: datascience.nih.gov/director/direc… #NIHData

Congrats to DataWorks! Challenge winners from our department! #N3C, led by Melissa Haendel, PhD, won the grand prize for #DataSharing, Monarch Initiative, won the Distinguished Achievement Award for #Data Reuse, and Krishnan Lab PhD, won the Significant Achievement Award for Data Reuse!

Excited to present new work led by Christopher Mancuso: GenePlexusZoo, a computational framework to improve discovering new genes linked to pathways, phenotypes, & diseases both within & across species by combining molecular networks from multiple species w/ #machinelearning. [1/n]

Excited to see fruits of a huge community effort! Thanks to Dr. Tijana Milenkovic for the leadership and the opportunity to be a part of this 🙌🏽

1/ Excited to share Txt2onto 2.0, an approach combining language models & machine learning to annotate public samples & studies with standardized tissue & disease terms with a focus on interpretability & explainability! 📜 doi.org/10.1101/2024.0… 💻 github.com/krishnanlab/tx… 🧵👇🏼

Preprint 🚨 A review state-of-the-art computational strategies for cross-species knowledge transfer in biomedicine 💻👩‍🦰🐭🐟🪰🪱🧬🫁⚕️ Led by an excellent team at Krishnan Lab: Hao Yuan, Christopher Mancuso, & @kaylainbio in collab w/ @FishEvoDevoGeno 🧵 arxiv.org/abs/2408.08503

📢#MLCB2024 Check out our recent review to break into translational biomedicine! We take a deep dive into methods for comparing & transferring data & knowledge across species, and highlight gaps/challenges. Details on implementation, data, & benchmarks: github.com/krishnanlab/cr…