AIMC Topic: Machine Learning

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CGBVS-DNN: Prediction of Compound-protein Interactions Based on Deep Learning.

Molecular informatics
Computational prediction of compound-protein interactions (CPIs) is of great importance for drug design as the first step in in-silico screening. We previously proposed chemical genomics-based virtual screening (CGBVS), which predicts CPIs by using a...

Machine Learned Replacement of N-Labels for Basecalled Sequences in DNA Barcoding.

IEEE/ACM transactions on computational biology and bioinformatics
This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to rep...

Adaptive control of nonlinear system using online error minimum neural networks.

ISA transactions
In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: onlin...

Mycofier: a new machine learning-based classifier for fungal ITS sequences.

BMC research notes
BACKGROUND: The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool ...

Approximate Bayesian MLP regularization for regression in the presence of noise.

Neural networks : the official journal of the International Neural Network Society
We present a novel regularization method for a multilayer perceptron (MLP) that learns a regression function in the presence of noise regardless of how smooth the function is. Unlike general MLP regularization methods assuming that a regression funct...

Calculation of upper esophageal sphincter restitution time from high resolution manometry data using machine learning.

Physiology & behavior
OBJECTIVE: After swallowing, the upper esophageal sphincter (UES) needs a certain amount of time to return from maximum pressure to the resting condition. Disturbances of sphincter function not only during the swallowing process but also in this phas...

DL-ADR: a novel deep learning model for classifying genomic variants into adverse drug reactions.

BMC medical genomics
BACKGROUND: Genomic variations are associated with the metabolism and the occurrence of adverse reactions of many therapeutic agents. The polymorphisms on over 2000 locations of cytochrome P450 enzymes (CYP) due to many factors such as ethnicity, mut...

Biomedical event trigger detection by dependency-based word embedding.

BMC medical genomics
BACKGROUND: In biomedical research, events revealing complex relations between entities play an important role. Biomedical event trigger identification has become a research hotspot since its important role in biomedical event extraction. Traditional...

Development of Health Parameter Model for Risk Prediction of CVD Using SVM.

Computational and mathematical methods in medicine
Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared th...

Adaptive Online Sequential ELM for Concept Drift Tackling.

Computational intelligence and neuroscience
A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM...