185 results on '"Schaduangrat, Nalini"'
Search Results
2. Stack-HDAC3i: A high-precision identification of HDAC3 inhibitors by exploiting a stacked ensemble-learning framework
3. StackER: a novel SMILES-based stacked approach for the accelerated and efficient discovery of ERα and ERβ antagonists
4. TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides
5. StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens
6. DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists
7. M3S-ALG: Improved and robust prediction of allergenicity of chemical compounds by using a novel multi-step stacking strategy
8. Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides
9. PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning
10. Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework
11. NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides
12. SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins
13. ABCpred: a webserver for the discovery of acetyl- and butyryl-cholinesterase inhibitors
14. StackPR is a new computational approach for large-scale identification of progesterone receptor antagonists using the stacking strategy
15. The role of ncRNA regulatory mechanisms in diseases—case on gestational diabetes
16. THPep: A machine learning-based approach for predicting tumor homing peptides
17. Leveraging a meta-learning approach to advance the accuracy of Nav blocking peptides prediction.
18. The role of ncRNA regulatory mechanisms in diseases—case on gestational diabetes.
19. TROLLOPE: A novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus
20. Pretoria: An effective computational approach for accurate and high-throughput identification of CD8+ t-cell epitopes of eukaryotic pathogens
21. Towards reproducible computational drug discovery
22. Contributors
23. Proteochemometric Modeling for Drug Repositioning
24. iAMAP-SCM: A Novel Computational Tool for Large-Scale Identification of Antimalarial Peptides Using Estimated Propensity Scores of Dipeptides
25. SCMRSA: a New Approach for Identifying and Analyzing Anti-MRSA Peptides Using Estimated Propensity Scores of Dipeptides
26. Empirical comparison and analysis of machine learning-based predictors for predicting and analyzing of thermophilic proteins
27. EMPIRICAL COMPARISON AND ANALYSIS OF MACHINE LEARNING-BASED APPROACHES FOR DRUGGABLE PROTEIN IDENTIFICATION.
28. ABCpred: a webserver for the discovery of acetyl- and butyryl-cholinesterase inhibitors
29. ERpred: a web server for the prediction of subtype-specific estrogen receptor antagonists
30. iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou's 5-Steps Rule and Informative Physicochemical Properties
31. RECENT DEVELOPMENT OF MACHINE LEARNING-BASED METHODS FOR THE PREDICTION OF DEFENSIN FAMILY AND SUBFAMILY.
32. Chapter 10 - Proteochemometric Modeling for Drug Repositioning
33. iBitter-SCM: Identification and characterization of bitter peptides using a scoring card method with propensity scores of dipeptides
34. HCVpred : A web server for predicting the bioactivity of hepatitis C virus NS5B inhibitors
35. HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation
36. Correction: Shoombuatong, W., et al. iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou’s 5-Steps Rule and Informative Physicochemical Properties. Int. J. Mol. Sci. 2020, 21, 75
37. PVPred-SCM: Improved Prediction and Analysis of Phage Virion Proteins Using a Scoring Card Method
38. iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides Using Informative Physicochemical Properties
39. Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation
40. Towards understanding aromatase inhibitory activity via QSAR modeling
41. Oxidative responses and defense mechanism of hyperpigmented P. aeruginosa as characterized by proteomics and metabolomics
42. Data mining for the identification of metabolic syndrome status
43. Unraveling the bioactivity of anticancer peptides as deduced from machine learning
44. TargetAntiAngio: A Sequence-Based Tool for the Prediction and Analysis of Anti-Angiogenic Peptides
45. ACPred: A Computational Tool for the Prediction and Analysis of Anticancer Peptides
46. Multidisciplinary approaches for targeting the secretase protein family as a therapeutic route for Alzheimer's disease
47. Tackling the Antibiotic Resistance Caused by Class A β-Lactamases through the Use of β-Lactamase Inhibitory Protein
48. PAAP: A Web Server for Predicting Antihypertensive Activity of Peptides
49. Probing the origin of estrogen receptor alpha inhibitionvialarge-scale QSAR study
50. Towards Predicting the Cytochrome P450 Modulation: From QSAR to Proteochemometric Modeling
Catalog
Books, media, physical & digital resources
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.