AIMC Topic: Software

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An open-source tool for analysis and automatic identification of dendritic spines using machine learning.

PloS one
Synaptic plasticity, the cellular basis for learning and memory, is mediated by a complex biochemical network of signaling proteins. These proteins are compartmentalized in dendritic spines, the tiny, bulbous, post-synaptic structures found on neuron...

Environmental properties of cells improve machine learning-based phenotype recognition accuracy.

Scientific reports
To answer major questions of cell biology, it is often essential to understand the complex phenotypic composition of cellular systems precisely. Modern automated microscopes produce vast amounts of images routinely, making manual analysis nearly impo...

PLANET-SNP pipeline: PLants based ANnotation and Establishment of True SNP pipeline.

Genomics
Acute prediction of SNPs (Single Nucleotide Polymorphisms) from high throughput sequencing data is a challenging problem, having potential to explore possible variation within plants species. For the extraction of profitable information from bulk of ...

A detailed analysis of the Arden Syntax expression grammar.

Journal of biomedical informatics
OBJECTIVE: The Arden Syntax for Medical Logic Systems is a standard for encoding and sharing medical knowledge in the form of Medical Logic Modules. To improve accessibility for clinicians, the originators of the standard deliberately designed Arden ...

Detection of Cattle Using Drones and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Multirotor drones have been one of the most important technological advances of the last decade. Their mechanics are simple compared to other types of drones and their possibilities in flight are greater. For example, they can take-off vertically. Th...

A meta-learning framework using representation learning to predict drug-drug interaction.

Journal of biomedical informatics
MOTIVATION: Predicting Drug-Drug Interaction (DDI) has become a crucial step in the drug discovery and development process, owing to the rise in the number of drugs co-administered with other drugs. Consequently, the usage of computational methods fo...

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

ACS chemical neuroscience
Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein...

Research on air pollutant concentration prediction method based on self-adaptive neuro-fuzzy weighted extreme learning machine.

Environmental pollution (Barking, Essex : 1987)
In order to improve the prediction accuracy and real-time of the air pollutant concentration prediction, this paper proposes self-adaptive neuro-fuzzy weighted extreme learning machine (ANFIS-WELM) based on the weighted extreme learning machine (WELM...

The past, present and future role of artificial intelligence in imaging.

European journal of radiology
Artificial intelligence (AI) is already widely employed in various medical roles, and ongoing technological advances are encouraging more widespread use of AI in imaging. This is partly driven by the recognition of the significant frequency and clini...

Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks.

Cell systems
Visualization algorithms are fundamental tools for interpreting single-cell data. However, standard methods, such as t-stochastic neighbor embedding (t-SNE), are not scalable to datasets with millions of cells and the resulting visualizations cannot ...