Pramod Bharadwaj Chandrashekar

14 posts

Pramod Bharadwaj Chandrashekar

Pramod Bharadwaj Chandrashekar

@domarp_cb

Wisconsin, USA Katılım Temmuz 2022
108 Takip Edilen11 Takipçiler
Pramod Bharadwaj Chandrashekar
Good morning #ASHG2025 👋 Come visit my poster to learn about our work on personalized functional genomics analysis for Alzheimer’s disease! 📍 Booth: 9225F
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Pramod Bharadwaj Chandrashekar
Excited to attend #ASHG2025! My research focuses on AI-driven personalized integration of multi-omics data to uncover disease heterogeneity. Actively exploring new research opportunities and look forward to connecting with researchers & potential collaborators.
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Center for Disease Neurogenomics
Center for Disease Neurogenomics@CDNeurogenomics·
For the personalized single-cell transcriptomics atlas of 1,494 brains, we developed iBrainMap, a graph-based model that prioritized personal cell-types, genes & networks, revealing new subtypes & population trajectories for #Alzheimers progression, cognition & NPS! #PsychAD
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Pokémon GO
Pokémon GO@PokemonGoApp·
What’s in the box? 👀 You can RT and find out! Roaming Form Gimmighoul can now be caught in #PokemonGO! We’re celebrating by giving away Gimmighoul-themed prizes!🥳🎉 To claim: Follow us on Twitter RT this post with #GOGimmighoul You’ll get a code to redeem. Let’s GO!
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Daifeng Wang
Daifeng Wang@daifengwang·
Our preprint introduces DeepGAMI, a single model that enables cross-modal imputation, predicts clinical phenotypes and prioritizes phenotypic tissue-/cell- type functional genomics for brains and brain diseases.
bioRxiv Bioinfo@biorxiv_bioinfo

DeepGAMI: Deep biologically guided auxiliary learning for multimodal integration and imputation to improve phenotype prediction biorxiv.org/cgi/content/sh… #biorxiv_bioinfo

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Daniel Gould, MD, PhD
Daniel Gould, MD, PhD@DJGould94·
The evolution of PhD student despair
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Pramod Bharadwaj Chandrashekar
Come check out my #MLCSB poster at #ISMB2022 at poster slot W-047 to know more about our work on deep auxiliary learning pipeline for integrating multi-modal data with cross-modality estimation. Looking forward to discuss with you guys during lunch.
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