AIMC Topic: Software

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Combined Machine Learning and Molecular Modelling Workflow for the Recognition of Potentially Novel Fungicides.

Molecules (Basel, Switzerland)
Novel machine learning and molecular modelling filtering procedures for drug repurposing have been carried out for the recognition of the novel fungicide targets of Cyp51 and Erg2. Classification and regression approaches on molecular descriptors hav...

Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?

European radiology
Digitization of medicine requires systematic handling of the increasing amount of health data to improve medical diagnosis. In this context, the integration of the versatile diagnostic information, e.g., from anamnesis, imaging, histopathology, and c...

Multifaceted analysis of training and testing convolutional neural networks for protein secondary structure prediction.

PloS one
Protein secondary structure prediction remains a vital topic with broad applications. Due to lack of a widely accepted standard in secondary structure predictor evaluation, a fair comparison of predictors is challenging. A detailed examination of fac...

An Open-Source Computer Vision Tool for Automated Vocal Fold Tracking From Videoendoscopy.

The Laryngoscope
OBJECTIVES: Contemporary clinical assessment of vocal fold adduction and abduction is qualitative and subjective. Herein is described a novel computer vision tool for automated quantitative tracking of vocal fold motion from videolaryngoscopy. The po...

Developing successful environmental decision support systems: Challenges and best practices.

Journal of environmental management
Environmental decision support systems (EDSSs), or DSS applied in the environmental field, have been developed for over 40 years now. However, most of these tools fail to find use or fall out of use extremely quickly. In the aim of aiding in the conc...

QUATgo: Protein quaternary structural attributes predicted by two-stage machine learning approaches with heterogeneous feature encoding.

PloS one
Many proteins exist in natures as oligomers with various quaternary structural attributes rather than as single chains. Predicting these attributes is an essential task in computational biology for the advancement of proteomics. However, the existing...

ASAP-SML: An antibody sequence analysis pipeline using statistical testing and machine learning.

PLoS computational biology
Antibodies are capable of potently and specifically binding individual antigens and, in some cases, disrupting their functions. The key challenge in generating antibody-based inhibitors is the lack of fundamental information relating sequences of ant...

Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability Domain .

Journal of chemical information and modeling
In ligand-based virtual screening, high-throughput screening (HTS) data sets can be exploited to train classification models. Such models can be used to prioritize yet untested molecules, from the most likely active (against a protein target of inter...

Machine learning volumetry of ischemic brain lesions on CT after thrombectomy-prospective diagnostic accuracy study in ischemic stroke patients.

Neuroradiology
PURPOSE: Ischemic lesion volume (ILV) is an important radiological predictor of functional outcome in patients with anterior circulation stroke. Our aim was to assess the agreement between automated ILV measurements on NCCT using the Brainomix softwa...

gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning.

Scientific reports
The biology of bacterial cells is, in general, based on information encoded on circular chromosomes. Regulation of chromosome replication is an essential process that mostly takes place at the origin of replication (oriC), a locus unique per chromoso...