@naimavahab.bsky.social
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reposted by
AI in Digital Health & Bioinformatics Lab
22 days ago
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...
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Multiโomics applications in health and diseases
Multi-omics research has transformed our ability to study biological systems by capturing information across multiple molecular layers, including genoโฆ
https://www.sciencedirect.com/science/chapter/bookseries/pii/S1877117326000128
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reposted by
Aashish Bhandari
about 1 month ago
Delighted to share the publication of our paper "๐ ๐ค๐ฐ๐ฎ๐ฑ๐ข๐ณ๐ข๐ต๐ช๐ท๐ฆ ๐ฆ๐ท๐ข๐ญ๐ถ๐ข๐ต๐ช๐ฐ๐ฏ ๐ฐ๐ง ๐ฉ๐ข๐ฏ๐ฅ๐ญ๐ช๐ฏ๐จ ๐ฎ๐ช๐ด๐ด๐ช๐ฏ๐จ ๐ฅ๐ข๐ต๐ข ๐ฑ๐ฐ๐ช๐ฏ๐ต๐ด ๐ข๐ฏ๐ฅ ๐ฎ๐ฐ๐ฅ๐ข๐ญ๐ช๐ต๐ช๐ฆ๐ด ๐ช๐ฏ ๐ฆ๐ญ๐ฆ๐ค๐ต๐ณ๐ฐ๐ฏ๐ช๐ค ๐ฉ๐ฆ๐ข๐ญ๐ต๐ฉ ๐ณ๐ฆ๐ค๐ฐ๐ณ๐ฅ๐ด" in the ๐๐ป๐๐ฒ๐ฟ๐ป๐ฎ๐๐ถ๐ผ๐ป๐ฎ๐น ๐๐ผ๐๐ฟ๐ป๐ฎ๐น ๐ผ๐ณ ๐ ๐ฒ๐ฑ๐ถ๐ฐ๐ฎ๐น ๐๐ป๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ฐ๐!
www.sciencedirect.com/science/arti...
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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 challengeโฆ
https://www.sciencedirect.com/science/article/pii/S1386505626000420
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reposted by
AI in Digital Health & Bioinformatics Lab
about 1 month ago
Congratulations
@aashishbhandari.com
๐
add a skeleton here at some point
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reposted by
AI in Digital Health & Bioinformatics Lab
4 months ago
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. ๐ Whatโs new: LLM-enabled clinical vocabulary mapping Support for FHIR A web-based interface ๐
papers.ssrn.com/sol3/papers....
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<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
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5534910
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reposted by
AI in Digital Health & Bioinformatics Lab
4 months ago
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 ๐
link.springer.com/article/10.1...
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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...
https://link.springer.com/article/10.1186/s44398-025-00012-7
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reposted by
AI in Digital Health & Bioinformatics Lab
4 months ago
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. ๐
www.nature.com/articles/s41...
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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
https://www.nature.com/articles/s41598-025-16701-2
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reposted by
Sonika Tyagi
4 months ago
New publication from the lab
add a skeleton here at some point
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reposted by
Sonika Tyagi
4 months ago
Our invited editorial in BMC Artificial Intelligence along with
@naimavahab.bsky.social
add a skeleton here at some point
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reposted by
Sonika Tyagi
about 1 year ago
#hotoffthepress
#newpublication
from the
#TyagiLab
"EHR-ML: A Data-Driven Framework for Designing Machine Learning Applications with Electronic Health Records โ Pre-proof is online now:
lnkd.in/gHHrFEGF
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LinkedIn
This link will take you to a page thatโs not on LinkedIn
https://lnkd.in/gHHrFEGF
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reposted by
AI in Digital Health & Bioinformatics Lab
11 months ago
Good work by
@aashishbhandari.com
#digitalhealth
#missingdata
#machinelearning
#predictivemodeling
#AIforHealth
add a skeleton here at some point
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reposted by
Sonika Tyagi
10 months ago
New publication from the lab
@tyagilab.bsky.social
Applications of linguistics in genome language modeling
academic.oup.com/biomethods/a...
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Genome language modeling (GLM): a beginnerโs cheat sheet
Abstract. Integrating genomics with diverse data modalities has the potential to revolutionize personalized medicine. However, this integration poses signi
https://academic.oup.com/biomethods/article/10/1/bpaf022/8093260
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reposted by
Sonika Tyagi
10 months ago
New publication from the lab
@tyagilab.bsky.social
academic.oup.com/biomethods/a...
#multimidaldata
#biomedicaldata
#dataharmonisation
#tyagilab
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Navigating the Multiverse: a Hitchhikerโs guide to selecting harmonization methods for multimodal biomedical data
Abstract. The application of machine learning (ML) techniques in predictive modelling has greatly advanced our comprehension of biological systems. There i
https://academic.oup.com/biomethods/article/doi/10.1093/biomethods/bpaf028/8115577?login=false
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reposted by
Sonika Tyagi
8 months ago
New preprint from the lab
@tyagilab.bsky.social
add a skeleton here at some point
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reposted by
AI in Digital Health & Bioinformatics Lab
7 months ago
#Interpretable
vs
#explainable
#AI
๐ An informative post by lab members
@esha4.bsky.social
and
@tnavya.bsky.social
๐
add a skeleton here at some point
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reposted by
AI in Digital Health & Bioinformatics Lab
7 months ago
#foundationsofAI
#AI
#teaching
add a skeleton here at some point
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reposted by
Sonika Tyagi
5 months ago
Congratulations to
@yashpalr.bsky.social
on his graduation!
@tyagilab.bsky.social
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reposted by
Aashish Bhandari
5 months ago
๐ฉบ 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. ๐
www.researchsquare.com/article/rs-6...
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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 individualโs health and lifestyle. This data can be harnessed for predictive modelling using machi...
https://www.researchsquare.com/article/rs-6117705/v1
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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
5 months ago
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