Search research articles
Contact Us
Filters
Showing results (1-10 of 67) with videos related to
Page
of 7
Sort By:
EXCLI Journal
|
September 8, 2018
Unraveling the bioactivity of anticancer peptides as deduced from machine learning
Watshara Shoombuatong, Nalini Schaduangrat, Chanin Nantasenamat
EXCLI Journal
|
October 2, 2023
Empirical comparison and analysis of machine learning-based approaches for druggable protein identification
Watshara Shoombuatong, Nalini Schaduangrat, Jaru Nikom
EXCLI Journal
|
May 29, 2018
Proteomic and bioinformatic discovery of biomarkers for diabetic nephropathy
Chadinee Thippakorn, Nalini Schaduangrat, Chanin Nantasenamat
EXCLI Journal
|
September 8, 2018
Towards understanding aromatase inhibitory activity via QSAR modeling
Watshara Shoombuatong, Nalini Schaduangrat, Chanin Nantasenamat
Scientific Reports
|
December 27, 2023
StackER: a novel SMILES-based stacked approach for the accelerated and efficient discovery of ERα and ERβ antagonists
Nalini Schaduangrat, Nutta Homdee, Watshara Shoombuatong
BMC Bioinformatics
|
July 28, 2023
StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens
Phasit Charoenkwan, Nalini Schaduangrat, Watshara Shoombuatong
Peerj
|
July 21, 2021
ERpred: a web server for the prediction of subtype-specific estrogen receptor antagonists
Nalini Schaduangrat, Aijaz Ahmad Malik, Chanin Nantasenamat
Methods (San Diego, Calif.)
|
December 21, 2024
Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides
Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, et al.
IEEE Transactions on Computational Biology and Bioinformatics
|
August 29, 2025
DeepHDAC3i: Leveraging an Interpretable Deep Learning-based Framework for the Accelerated Discovery of HDAC3 Inhibitors
Saeed Ahmed, Nalini Schaduangrat, Ittipat Meewan, et al.
EXCLI Journal
|
February 1, 2018
Data mining for the identification of metabolic syndrome status
Apilak Worachartcheewan, Nalini Schaduangrat, Virapong Prachayasittikul, et al.
Page
of 7
Search research articles
Search
Showing results (1-10 of 67) with videos related to
Sort By:
Page
of 7
EXCLI Journal
|
September 8, 2018
Unraveling the bioactivity of anticancer peptides as deduced from machine learning
Watshara Shoombuatong, Nalini Schaduangrat, Chanin Nantasenamat
EXCLI Journal
|
October 2, 2023
Empirical comparison and analysis of machine learning-based approaches for druggable protein identification
Watshara Shoombuatong, Nalini Schaduangrat, Jaru Nikom
EXCLI Journal
|
May 29, 2018
Proteomic and bioinformatic discovery of biomarkers for diabetic nephropathy
Chadinee Thippakorn, Nalini Schaduangrat, Chanin Nantasenamat
EXCLI Journal
|
September 8, 2018
Towards understanding aromatase inhibitory activity via QSAR modeling
Watshara Shoombuatong, Nalini Schaduangrat, Chanin Nantasenamat
Scientific Reports
|
December 27, 2023
StackER: a novel SMILES-based stacked approach for the accelerated and efficient discovery of ERα and ERβ antagonists
Nalini Schaduangrat, Nutta Homdee, Watshara Shoombuatong
BMC Bioinformatics
|
July 28, 2023
StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens
Phasit Charoenkwan, Nalini Schaduangrat, Watshara Shoombuatong
Peerj
|
July 21, 2021
ERpred: a web server for the prediction of subtype-specific estrogen receptor antagonists
Nalini Schaduangrat, Aijaz Ahmad Malik, Chanin Nantasenamat
Methods (San Diego, Calif.)
|
December 21, 2024
Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides
Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, et al.
IEEE Transactions on Computational Biology and Bioinformatics
|
August 29, 2025
DeepHDAC3i: Leveraging an Interpretable Deep Learning-based Framework for the Accelerated Discovery of HDAC3 Inhibitors
Saeed Ahmed, Nalini Schaduangrat, Ittipat Meewan, et al.
EXCLI Journal
|
February 1, 2018
Data mining for the identification of metabolic syndrome status
Apilak Worachartcheewan, Nalini Schaduangrat, Virapong Prachayasittikul, et al.
Page
of 7