AIMC Topic: Animals

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Deep learning for molecular generation.

Future medicinal chemistry
De novo drug design aims to generate novel chemical compounds with desirable chemical and pharmacological properties from scratch using computer-based methods. Recently, deep generative neural networks have become a very active research frontier in d...

An ecologically constrained procedure for sensitivity analysis of Artificial Neural Networks and other empirical models.

PloS one
Sensitivity analysis applied to Artificial Neural Networks (ANNs) as well as to other types of empirical ecological models allows assessing the importance of environmental predictive variables in affecting species distribution or other target variabl...

Aeromonas hydrophila biofilm, exoprotease, and quorum sensing responses to co-cultivation with diverse foodborne pathogens and food spoilage bacteria on crab surfaces.

Biofouling
The effects of dual species interactions on biofilm formation by Aeromonas hydrophila in the presence of Pseudomonas aeruginosa, Pseudomonas fluorescens, Pectobacterium carotovorum, Salmonella Typhimurium, and Listeria monocytogenes were examined. Hi...

Attribute selection and model evaluation for the maternal and paternal imprinted genes in bovine (Bos Taurus) using supervised machine learning algorithms.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
Imprinted genes display biased expression of paternal and maternal alleles in mammals. They are marked through epigenetic process during gametogenesis. Characterization of imprinted genes has expanded our understanding of the regulation and function ...

Machine Learning and Integrative Analysis of Biomedical Big Data.

Genes
Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., gen...

In silico prediction of chemical reproductive toxicity using machine learning.

Journal of applied toxicology : JAT
Reproductive toxicity is an important regulatory endpoint in health hazard assessment. Because the in vivo tests are expensive, time consuming and require a large number of animals, which must be killed, in silico approaches as the alternative strate...

Prior Information Guided Regularized Deep Learning for Cell Nucleus Detection.

IEEE transactions on medical imaging
Cell nuclei detection is a challenging research topic because of limitations in cellular image quality and diversity of nuclear morphology, i.e., varying nuclei shapes, sizes, and overlaps between multiple cell nuclei. This has been a topic of enduri...

Comparative Study of Multitask Toxicity Modeling on a Broad Chemical Space.

Journal of chemical information and modeling
Acute toxicity is one of the most challenging properties to predict purely with computational methods due to its direct relationship to biological interactions. Moreover, toxicity can be represented by different end points: it can be measured for dif...

Robotic device shows lack of momentum enhancement for gymnotiform swimmers.

Bioinspiration & biomimetics
Many fish generate thrust by undulating one or multiple elongated fins while keeping their body straight. This propulsion mechanism has stimulated interest in both biology and bio-inspired marine propulsion because its maneuverability and efficiency ...

Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives.

Human genetics
In the field of cancer genomics, the broad availability of genetic information offered by next-generation sequencing technologies and rapid growth in biomedical publication has led to the advent of the big-data era. Integration of artificial intellig...