AIMC Topic: Animals

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Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity.

European journal of medicinal chemistry
Primaquine (PQ) is a commonly used drug that can prevent the transmission of Plasmodium falciparum malaria, however toxicity limits its use. We prepared five groups of PQ derivatives: amides 1a-k, ureas 2a-k, semicarbazides 3a,b, acylsemicarbazides 4...

A Shared Vision for Machine Learning in Neuroscience.

The Journal of neuroscience : the official journal of the Society for Neuroscience
With ever-increasing advancements in technology, neuroscientists are able to collect data in greater volumes and with finer resolution. The bottleneck in understanding how the brain works is consequently shifting away from the amount and type of data...

Body stiffness in orthogonal directions oppositely affects worm-like robot turning and straight-line locomotion.

Bioinspiration & biomimetics
Earthworms locomote using traveling waves of segment contraction and expansion, which when symmetric result in straight-line locomotion and when biased result in turning. The mechanics of the soft body permit a large range of possible body shapes whi...

Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM).

Current protocols in cytometry
Multiplexed single-cell experimental techniques like mass cytometry measure 40 or more features and enable deep characterization of well-known and novel cell populations. However, traditional data analysis techniques rely extensively on human experts...

Brain maps 4.0-Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps.

The Journal of comparative neurology
The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature table...

Application of a Deep Neural Network to Metabolomics Studies and Its Performance in Determining Important Variables.

Analytical chemistry
Deep neural networks (DNNs), which are kinds of the machine learning approaches, are powerful tools for analyzing big sets of data derived from biological and environmental systems. However, DNNs are not applicable to metabolomics studies because the...

WorMachine: machine learning-based phenotypic analysis tool for worms.

BMC biology
BACKGROUND: Caenorhabditis elegans nematodes are powerful model organisms, yet quantification of visible phenotypes is still often labor-intensive, biased, and error-prone. We developed WorMachine, a three-step MATLAB-based image analysis software th...

Enhanced Ant Colony Optimization with Dynamic Mutation and Ad Hoc Initialization for Improving the Design of TSK-Type Fuzzy System.

Computational intelligence and neuroscience
This paper proposes an enhanced ant colony optimization with dynamic mutation and ad hoc initialization, ACODM-I, for improving the accuracy of Takagi-Sugeno-Kang- (TSK-) type fuzzy systems design. Instead of the generic initialization usually used i...

Combining machine learning models of in vitro and in vivo bioassays improves rat carcinogenicity prediction.

Regulatory toxicology and pharmacology : RTP
In vitro genotoxicity bioassays are cost-efficient methods of assessing potential carcinogens. However, many genotoxicity bioassays are inappropriate for detecting chemicals eliciting non-genotoxic mechanisms, such as tumour promotion, this necessita...

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack...