Krishnan Lab

Laboratory for Biomedical Data Science and Computational Genomics at @CUBiomedInfo and @CUHealthAI | @[email protected]

[Arjun Krishnan @compbiologist]

📢#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: https://t.co/iEWv1LwnbX

[Arjun Krishnan @compbiologist]

Preprint 🚨
A review state-of-the-art computational strategies for cross-species knowledge transfer in biomedicine
💻👩‍🦰🐭🐟🪰🪱🧬🫁⚕️

Led by an excellent team at @KrishnanLab: @yhbioinfo, @ChrisAMancuso, & @kaylainbio in collab w/ @FishEvoDevoGeno 🧵

https://t.co/nbVdKALnXm

[Arjun Krishnan @compbiologist]

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!

📜 https://t.co/iZYPSGGQvp
💻 https://t.co/aOvuy75Rbh

🧵👇🏼

[Arjun Krishnan @compbiologist]

Excited to see fruits of a huge community effort! Thanks to @ProfMilenkovic for the leadership and the opportunity to be a part of this 🙌🏽

[Arjun Krishnan @compbiologist]

Excited to present new work led by @ChrisAMancuso:
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]

[NIH Office of Data Science Strategy @NIHDataScience]

🎉CONGRATS to the winners of the @FASEBorg 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:
https://t.co/1oeYEG8pja #NIHData

[CU Department of Biomedical Informatics (DBMI) @CUBiomedInfo]

Congrats to DataWorks! Challenge winners from our department! #N3C, led by @ontowonka, PhD, won the grand prize for #DataSharing, @MonarchInit, won the Distinguished Achievement Award for #Data Reuse, and @KrishnanLab PhD, won the Significant Achievement Award for Data Reuse!

[Subu Ramanathan @SPRamanathan]

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!

https://t.co/1uANtGixhH

Please RT!

[CU Department of Biomedical Informatics (DBMI) @CUBiomedInfo]

Three @CUAnschutz teams are DataWorks prize finalists! Learn more about @KrishnanLab, @MonarchInit, and #NationalCovidCohortCollaborative's projects and vote for one here👇

[CU Department of Biomedical Informatics (DBMI) @CUBiomedInfo]

A new software created by @compbiologist, PhD, associate professor of biomedical informatics at @CUMedicalSchool, and his team, annotates genomics samples based on unstructured sample text descriptions, making them easier for researchers to find and use.👇
https://t.co/Z3pn2Of8Cq

[Nature Communications @NatureComms]

The @KrishnanLab 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 @compbiologist

https://t.co/Xf2VmFakBf

[Arjun Krishnan @compbiologist]

This wk, @kaylainbio defended her brilliant PhD work on using #transcriptomes, #networks, & #machinelearning to probe age- & sex-specificity 🎉

Being the first grad student from @KrishnanLab, Kayla has set a v. high bar!

Congratulations Dr. Johnson! We're very proud of you!!

[Arjun Krishnan @compbiologist]

🎇 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!
https://t.co/6VpeFll6kq

[Nature Communications @NatureComms]

The @KrishnanLab 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 @compbiologist

https://t.co/Xf2VmFakBf

[Clint Miller @clintomics]

Automated NLP and ML approach to annotate samples to their tissue-of-origin by modeling unstructured metadata. Improved performance and scalability compared to MetaSRA ⁦@NatureComms⁩ ⁦@compbiologist⁩ https://t.co/Mh2wRsCJPn

[Arjun Krishnan @compbiologist]

The Computational Biosciences PhD Program @CUAnschutz 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. https://t.co/O1KZ7EZ05m

[Arjun Krishnan @compbiologist]

Two posters in @MlcsbC #ISMB2022

@NeutralYh | W-058
Cross-species transcriptome-based regression to discover model equivalents of human samples & genes. w/ @ingo_braasch

@filjev46 | W-067
Determining the optimal embedding technique for mapping transcriptomes to ontologies

[Arjun Krishnan @compbiologist]

We have 3 posters at @TransMedISMB #ISMB2022

@kaylainbio | N-023
Age- and sex-specific gene signatures and networks

@slepphickey | N-024
Chronic inflammation network signatures in complex diseases

@KewalinSamart | Virtual
Drug repurposing for infectious diseases w/ @janani137

[Arjun Krishnan @compbiologist]

We have 2 posters at #NetBio #ISMB2022

@ChrisAMancuso | 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

[Arjun Krishnan @compbiologist]

On Wed, July 13, @ChrisAMancuso is giving a talk in @OBF_BOSC #BOSC on "GenePlexus: A web server and Python package for gene discovery using network-based machine learning"

Paper: https://t.co/HnqpUHr1AO
Webserver: https://t.co/UD84qmDeRS
Repo: https://t.co/BMCVTl06HP

#ISMB2022