[HTML][HTML] Quantitative structure activity relationship study of the anti-hepatitis peptides employing random forests and extra-trees regressors

G Mishra, D Sehgal, JK Valadi - Bioinformation, 2017 - ncbi.nlm.nih.gov
Antimicrobial peptides are host defense peptides being viewed as replacement to broad-
spectrum antibiotics due to varied advantages. Hepatitis is the commonest infectious …

[HTML][HTML] dsAMP and dsAMPGAN: Deep Learning Networks for Antimicrobial Peptides Recognition and Generation

M Zhao, Y Zhang, M Wang, LZ Ma - Antibiotics, 2024 - pmc.ncbi.nlm.nih.gov
Antibiotic resistance is a growing public health challenge. Antimicrobial peptides (AMPs)
effectively target microorganisms through non-specific mechanisms, limiting their ability to …

Tuning the parameters of weighted ELM using IWO and BAT algorithm to improve the classification performance

S Priya, R Manavalan - 2018 2nd international conference on I …, 2018 - ieeexplore.ieee.org
Weighted Extreme Learning Machine (WELM) is one among the machine learning
algorithms with extremely learning and good generalization capabilities. WELM handles the …

Hybrid Intelligent Techniques in Text Mining and Analysis of Social Networks and Media Data

N Golani, I Khandelwal, BK Tripathy - Hybrid Intelligence for Social …, 2017 - Springer
Text data from social media and networks are ubiquitous and are emerging at a high rate.
Tackling these bulky text data has become a challenging task and an important field of …

Performance Analysis of Nature-Inspired Algorithms-Based Bayesian Prediction Models for Medical Data Sets

A Kumar, BK Sarkar - Research Anthology on Multi-Industry Uses of …, 2021 - igi-global.com
Research in medical data prediction has become an important classification problem due to
its domain specificity, voluminous, and class imbalanced nature. In this chapter, four well …

Diabetes risk stratification method based on fuzzy logic and bio-inspired meta-heuristics

A Deme, VR Chifu, CB Pop… - International Journal …, 2019 - inderscienceonline.com
This paper presents a system for diabetes risk stratification that combines fuzzy logic with
two bio-inspired algorithms. The developed system takes as input a set of patients described …