iiinova — where your digital self keeps evolving

Reposted by Aashish Bhandari

AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 04/09/2026

lnkd.in/p/gTtrqTku PregBase is published in 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗶𝗻 𝗠𝗲𝗱𝗶𝗰𝗶𝗻𝗲. The first comprehensive knowledge base designed specifically for pregnancy research. Try it: pregknowledgebase.com Read the full paper: lnkd.in/gs7W9KdS #PregBase #MaternalHealth #PhD #RMIT #DigitalHealth #TyagiLab

lnkd.in

New research out of STEM College has developed PregBase - the first knowledge base built specifically to bring together decades of pregnancy research in one place. PregBase is an AI system that… | RM...

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Reposted by Aashish Bhandari

abacbs.bsky.social @abacbs.bsky.social · 02/03/2026

We are delighted to announce that #ABACBS2026 will be held at RMIT, Melbourne CBD campus from 16th to 20th November 2026. Big thanks to A/Prof. Sonika Tyagi and team for leading this years organising! More details and official conference launch to follow! #bioinformatics @combine1.bsky.social

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Reposted by Aashish Bhandari

Sonika Tyagi @tsonika.bsky.social · 06/03/2026

🔊Applications invited: hashtag#Funded BITS–RMIT hashtag#PhD program offering international experience. We have two #WomenHealth oriented #DigitalHealth projects listed. These projects are designed to look at unique Australian and Indian context of different womens health outcome questions.

lnkd.in

This link will take you to a page that’s not on LinkedIn

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Reposted by Aashish Bhandari

AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 30/01/2026

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...

sciencedirect.com

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…

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Aashish Bhandari @aashishbhandari.com · 21/01/2026

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...

sciencedirect.com

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…

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Reposted by Aashish Bhandari

AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 25/09/2025

Research published in 2024 by our lab member @naimavahab.bsky.social and continue to use this for future work on elucidating biological regulatory pathways.

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Reposted by Aashish Bhandari

AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 13/10/2025

DM us for online meeting link

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Reposted by Aashish Bhandari

AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 14/10/2025

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...

nature.com

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

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Reposted by Aashish Bhandari

AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 14/10/2025

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...

link.springer.com

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...

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Reposted by Aashish Bhandari

AI in Digital Health & Bioinformatics Lab @tyagilab.bsky.social · 14/10/2025

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....

papers.ssrn.com

<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

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Aashish Bhandari @aashishbhandari.com · 25/09/2025

🩺 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...

researchsquare.com

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...

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