Aashish Bhandari
aashishbhandari.com
Aashish Bhandari
@aashishbhandari.com
PhD student @ RMIT

#machinelearning #digitalhealth
Reposted by Aashish Bhandari
A book chapter from the lab:

This chapter explores multi-omics integrative studies enabled by machine learning, presenting an overview of state-of-the-art methodologies and the foundational background. Suitable for both beginners & advanced bioinformaticians
www.sciencedirect.com/science/chap...
Multi‐omics applications in health and diseases
Multi-omics research has transformed our ability to study biological systems by capturing information across multiple molecular layers, including geno…
www.sciencedirect.com
January 30, 2026 at 10:13 PM
Delighted to share the publication of our paper "𝘈 𝘤𝘰𝘮𝘱𝘢𝘳𝘢𝘵𝘪𝘷𝘦 𝘦𝘷𝘢𝘭𝘶𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘩𝘢𝘯𝘥𝘭𝘪𝘯𝘨 𝘮𝘪𝘴𝘴𝘪𝘯𝘨 𝘥𝘢𝘵𝘢 𝘱𝘰𝘪𝘯𝘵𝘴 𝘢𝘯𝘥 𝘮𝘰𝘥𝘢𝘭𝘪𝘵𝘪𝘦𝘴 𝘪𝘯 𝘦𝘭𝘦𝘤𝘵𝘳𝘰𝘯𝘪𝘤 𝘩𝘦𝘢𝘭𝘵𝘩 𝘳𝘦𝘤𝘰𝘳𝘥𝘴" in the 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗝𝗼𝘂𝗿𝗻𝗮𝗹 𝗼𝗳 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀!

www.sciencedirect.com/science/arti...
A comparative evaluation of handling missing data points and modalities in electronic health records
Background: Healthcare data, generally available as electronic health records (EHR), provide rich insight for predictive modelling. A common challenge…
www.sciencedirect.com
January 21, 2026 at 11:28 PM
Reposted by Aashish Bhandari
New publication from the lab @tyagilab.bsky.social

Applications of linguistics in genome language modeling

academic.oup.com/biomethods/a...
Genome language modeling (GLM): a beginner’s cheat sheet
Abstract. Integrating genomics with diverse data modalities has the potential to revolutionize personalized medicine. However, this integration poses signi
academic.oup.com
May 12, 2025 at 1:06 AM
Reposted by Aashish Bhandari
Research published in 2024 by our lab member @naimavahab.bsky.social and continue to use this for future work on elucidating biological regulatory pathways.
A versatile machine learning pipeline to find co-regulatory modules (CRMs) in DNA.
Check it out and explore: doi.org/10.1016/j.co...

#Genomics #Epigenomics #MachineLearning #CardiacResearch #OpenScience

@tyagilab.bsky.social @tsonika.bsky.social
September 25, 2025 at 4:24 AM
Reposted by Aashish Bhandari
DM us for online meeting link
October 13, 2025 at 10:26 AM
Reposted by Aashish Bhandari
Our latest paper combines multi-omics integration with genome-scale NLP models trained on DNA to uncover how S. aureus regulates infection, metabolism, and antibiotic resistance.

This unique organism agnostic method offers a new lens for systems-level biology.

🔗 www.nature.com/articles/s41...
Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models - Scientific Reports
Scientific Reports - Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models
www.nature.com
October 14, 2025 at 9:11 PM
Reposted by Aashish Bhandari
Our latest review explores how RNA foundation models are reshaping predictions of ncRNA structure & function.

We highlight key architectures, training strategies, and open challenges to guide the next phase of RNA-AI research.

Read here 👉 link.springer.com/article/10.1...
Advancing non-coding RNA annotation with RNA sequence foundation models: structure and function perspectives - BMC Artificial Intelligence
Noncoding RNAs (ncRNAs) form the major part of the expressed transcriptome. These are critical in regulating gene expression and contributing to disease mechanisms, primarily through their complex sec...
link.springer.com
October 14, 2025 at 9:18 PM
Reposted by Aashish Bhandari
Our latest paper presents EHR-QC 2.0, a major upgrade to our open-source pipeline for preparing and standardising biomedical & genomic EHR data for machine learning.

🔍 What’s new:

LLM-enabled clinical vocabulary mapping

Support for FHIR

A web-based interface

🔗 papers.ssrn.com/sol3/papers....
<span>An accessible pipeline for LLM-driven medical concept mapping, automated OMOP and FHIR conversion</span>
Background:Our previous work introduced the open-source EHR-QC pipeline. This pipeline implements extraction, transform and load (ETL), pre-processing and quali
papers.ssrn.com
October 14, 2025 at 9:25 PM
🩺 Missing medical data isn't just something to fill in or ignore!
EHRs often have missing values. Common fix? Imputation. But filling gaps can mislead predictions.
We explore ML approaches to handle missingness while preserving the original data distribution.
📜 www.researchsquare.com/article/rs-6...
Mind the Gaps: Guess Less, Predict More with Missing Medical Data
Healthcare data, generally available as electronic health records (EHR), provide a rich profile of an individual’s health and lifestyle. This data can be harnessed for predictive modelling using machi...
www.researchsquare.com
September 25, 2025 at 1:33 AM