User profiles for U Deva Priyakumar
U. Deva PriyakumarProfessor, IIIT Hyderabad Verified email at iiit.ac.in Cited by 4183 |
Structure-based drug repurposing: Traditional and advanced AI/ML-aided methods
Highlights • Repurposing existing drugs for new diseases is cost effective and time saving. •
In silico methods are crucial for rapid drug screening in the early stages. • Machine learning …
In silico methods are crucial for rapid drug screening in the early stages. • Machine learning …
Impact of 2′‐hydroxyl sampling on the conformational properties of RNA: update of the CHARMM all‐atom additive force field for RNA
EJ Denning, UD Priyakumar, L Nilsson… - Journal of …, 2011 - Wiley Online Library
Here, we present an update of the CHARMM27 all‐atom additive force field for nucleic
acids that improves the treatment of RNA molecules. The original CHARMM27 force field …
acids that improves the treatment of RNA molecules. The original CHARMM27 force field …
[HTML][HTML] Machine learning based clinical decision support system for early COVID-19 mortality prediction
The coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, is an acute
respiratory disease that has been classified as a pandemic by the World Health Organization (…
respiratory disease that has been classified as a pandemic by the World Health Organization (…
DeepPocket: ligand binding site detection and segmentation using 3D convolutional neural networks
A structure-based drug design pipeline involves the development of potential drug
molecules or ligands that form stable complexes with a given receptor at its binding site. A …
molecules or ligands that form stable complexes with a given receptor at its binding site. A …
MolGPT: molecular generation using a transformer-decoder model
Application of deep learning techniques for de novo generation of molecules, termed as
inverse molecular design, has been gaining enormous traction in drug design. The …
inverse molecular design, has been gaining enormous traction in drug design. The …
Mmbert: Multimodal bert pretraining for improved medical vqa
…, M Mathew, A Devi, UD Priyakumar… - 2021 IEEE 18th …, 2021 - ieeexplore.ieee.org
Images in the medical domain are fundamentally different from the general domain images.
Consequently, it is infeasible to directly employ general domain Visual Question Answering (…
Consequently, it is infeasible to directly employ general domain Visual Question Answering (…
Molecular representations for machine learning applications in chemistry
S Raghunathan, UD Priyakumar - International Journal of …, 2022 - Wiley Online Library
Abstract Machine learning (ML) methods enable computers to address problems by learning
from existing data. Such applications are becoming commonplace in molecular sciences. …
from existing data. Such applications are becoming commonplace in molecular sciences. …
Host metabolic reprogramming in response to SARS-CoV-2 infection: A systems biology approach
Understanding the pathogenesis of SARS-CoV-2 is essential for developing effective
treatment strategies. Viruses hijack the host metabolism to redirect the resources for their …
treatment strategies. Viruses hijack the host metabolism to redirect the resources for their …
Modern machine learning for tackling inverse problems in chemistry: molecular design to realization
The discovery of new molecules and materials helps expand the horizons of novel and
innovative real-life applications. In pursuit of finding molecules with desired properties, chemists …
innovative real-life applications. In pursuit of finding molecules with desired properties, chemists …
[HTML][HTML] Memes: Machine learning framework for enhanced molecular screening
In drug discovery applications, high throughput virtual screening exercises are routinely
performed to determine an initial set of candidate molecules referred to as “hits”. In such an …
performed to determine an initial set of candidate molecules referred to as “hits”. In such an …