AIMC Topic: Machine Learning

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ROCS-derived features for virtual screening.

Journal of computer-aided molecular design
Rapid overlay of chemical structures (ROCS) is a standard tool for the calculation of 3D shape and chemical ("color") similarity. ROCS uses unweighted sums to combine many aspects of similarity, yielding parameter-free models for virtual screening. I...

Fault Diagnosis for Analog Circuits by Using EEMD, Relative Entropy, and ELM.

Computational intelligence and neuroscience
This paper presents a novel fault diagnosis method for analog circuits using ensemble empirical mode decomposition (EEMD), relative entropy, and extreme learning machine (ELM). First, nominal and faulty response waveforms of a circuit are measured, r...

The LET Procedure for Prosthetic Myocontrol: Towards Multi-DOF Control Using Single-DOF Activations.

PloS one
Simultaneous and proportional myocontrol of dexterous hand prostheses is to a large extent still an open problem. With the advent of commercially and clinically available multi-fingered hand prostheses there are now more independent degrees of freedo...

The Next Era: Deep Learning in Pharmaceutical Research.

Pharmaceutical research
Over the past decade we have witnessed the increasing sophistication of machine learning algorithms applied in daily use from internet searches, voice recognition, social network software to machine vision software in cameras, phones, robots and self...

A D3R prospective evaluation of machine learning for protein-ligand scoring.

Journal of computer-aided molecular design
We assess the performance of several machine learning-based scoring methods at protein-ligand pose prediction, virtual screening, and binding affinity prediction. The methods and the manner in which they were trained make them sufficiently diverse to...

An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

Methods (San Diego, Calif.)
Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differe...

Single Molecule Fluorescence Microscopy and Machine Learning for Rhesus D Antigen Classification.

Scientific reports
In transfusion medicine, the identification of the Rhesus D type is important to prevent anti-D immunisation in Rhesus D negative recipients. In particular, the detection of the very low expressed DEL phenotype is crucial and hence constitutes the bo...

hMuLab: A Biomedical Hybrid MUlti-LABel Classifier Based on Multiple Linear Regression.

IEEE/ACM transactions on computational biology and bioinformatics
Many biomedical classification problems are multi-label by nature, e.g., a gene involved in a variety of functions and a patient with multiple diseases. The majority of existing classification algorithms assumes each sample with only one class label,...

Automated detection of discourse segment and experimental types from the text of cancer pathway results sections.

Database : the journal of biological databases and curation
Automated machine-reading biocuration systems typically use sentence-by-sentence information extraction to construct meaning representations for use by curators. This does not directly reflect the typical discourse structure used by scientists to con...