AIMC Topic: Animals

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Active Inference and Intentional Behavior.

Neural computation
Recent advances in theoretical biology suggest that key definitions of basal cognition and sentient behavior may arise as emergent properties of in vitro cell cultures and neuronal networks. Such neuronal networks reorganize activity to demonstrate s...

The Unified Phenotype Ontology : a framework for cross-species integrative phenomics.

Genetics
Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype...

A deep learning tissue classifier based on differential co-expression genes predicts the pregnancy outcomes of cattle†.

Biology of reproduction
Economic losses in cattle farms are frequently associated with failed pregnancies. Some studies found that the transcriptomic profiles of blood and endometrial tissues in cattle with varying pregnancy outcomes display discrepancies even before artifi...

MAEST: accurately spatial domain detection in spatial transcriptomics with graph masked autoencoder.

Briefings in bioinformatics
Spatial transcriptomics (ST) technology provides gene expression profiles with spatial context, offering critical insights into cellular interactions and tissue architecture. A core task in ST is spatial domain identification, which involves detectin...

Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models.

Molecular informatics
The blood brain barrier (BBB) is an endothelial-derived structure which restricts the movement of certain molecules between the general somatic circulatory system to the central nervous system (CNS). While the BBB maintains homeostasis by regulating ...

Classification of Bryde's whale individuals using high-resolution time-frequency transforms and support vector machines.

The Journal of the Acoustical Society of America
Whales generate vocalizations which may, deliberately or not, encode caller identity cues. In this study, we analyze calls produced by Bryde's whales and recorded by ocean-bottom arrays of hydrophones deployed close to the Costa Rica Rift in the Pana...

Machine Learning-Based Glycolipid Metabolism Gene Signature Predicts Prognosis and Immune Landscape in Oesophageal Squamous Cell Carcinoma.

Journal of cellular and molecular medicine
Using machine learning approaches, we developed and validated a novel prognostic model for oesophageal squamous cell carcinoma (ESCC) based on glycolipid metabolism-related genes. Through integrated analysis of TCGA and GEO datasets, we established a...

Machine Learning Models Based on Stretched-Exponential Diffusion Weighted Imaging to Predict TROP2 Expression in Nude Mouse Breast Cancer Models.

Discovery medicine
BACKGROUND: Trophoblast cell surface antigen 2 (TROP2) is a promising target for various cancers, including breast cancer. The development of noninvasive techniques for assessing TROP2 expression in tumors holds considerable importance. This study ai...

ML-UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper.

Physiological reports
The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution of urine spot patterns on filter paper with software remains problematic due to inter-laboratory di...

Predicting Pharmacokinetics in Rats Using Machine Learning: A Comparative Study Between Empirical, Compartmental, and PBPK-Based Approaches.

Clinical and translational science
A successful drug needs to combine several properties including high potency and good pharmacokinetic (PK) properties to sustain efficacious plasma concentration over time. To estimate required doses for preclinical animal efficacy models or for the ...