AIMC Topic: Animals

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Genome Mining and Chemistry-Driven Discovery of a Cell Wall Lipopeptide Signature for subsp. Ancestral Lineage.

ACS infectious diseases
subsp. () causes Johne's disease (JD), a chronic infection responsible for considerable economic losses to dairy industries worldwide. Genetically clonal, has evolved into three distinct genetic lineages designated CII, for bovine strains, and SI ...

The combined multilayer perceptron and logistic regression (MLP-LR) method better predicted the spread of Hyphantria cunea (Lepidoptera: Erebidae).

Journal of economic entomology
Hyphantria cunea (Lepidoptera: Erebidae) is one of the pests that pose a serious threat to forest and agronomic crops in China. Its spread is influenced by various factors, including environmental factors and anthropogenic factors, and the available ...

Comparing point counts, passive acoustic monitoring, citizen science and machine learning for bird species monitoring in the Mount Kenya ecosystem.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Biodiversity loss is a pressing challenge, with ecosystems across the world under threat from factors such as human encroachment, over exploitation and climate change. It is important to increase ecosystem monitoring efforts to provide actionable ins...

Using tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Machine learning has the potential to revolutionize passive acoustic monitoring (PAM) for ecological assessments. However, high annotation and computing costs limit the field's adoption. Generalizable pretrained networks can overcome these costs, but...

Integrating Deep Learning Derived Morphological Traits and Molecular Data for Total-Evidence Phylogenetics: Lessons from Digitized Collections.

Systematic biology
Deep learning has previously shown success in automatically generating morphological traits that carry a phylogenetic signal. In this paper, we explore combining molecular data with deep learning derived morphological traits from images of pinned ins...

Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex.

Parasites & vectors
BACKGROUND: Mosquito-borne diseases, such as malaria, dengue, and Zika, continue to pose significant threats to global health, resulting in millions of cases and thousands of deaths each year. Notably, only older mosquitoes can transmit these disease...

Computationally designed proteins mimic antibody immune evasion in viral evolution.

Immunity
Recurrent waves of viral infection necessitate vaccines and therapeutics that remain effective against emerging viruses. Our ability to evaluate interventions is currently limited to assessments against past or circulating variants, which likely diff...

Beyond 3D Printing: How AI is Shaping the Future of Craniomaxillofacial Bone Tissue Engineering.

ACS biomaterials science & engineering
This perspective focuses on the potential of artificial intelligence (AI) in craniomaxillofacial (CMF) bone tissue engineering, mitigating current challenges, and driving the development of tailored biomaterials and clinical translation. CMF bone tis...

To Fly, or Not to Fly, That Is the Question: A Deep Learning Model for Peptide Detectability Prediction in Mass Spectrometry.

Journal of proteome research
Identifying detectable peptides, known as flyers, is key in mass spectrometry-based proteomics. Peptide detectability is strongly related to peptide sequences and their resulting physicochemical properties. Moreover, the high variability in MS data c...

Predicting Bioconcentration Factors of Per- and Polyfluoroalkyl Substances Using a Directed Message Passing Neural Network with Multimodal Feature Fusion.

Environmental science & technology
Amid growing concerns regarding the ecological risks posed by emerging contaminants, per- and polyfluoroalkyl substances (PFASs) present significant challenges for risk assessment due to their structural diversity and the paucity of experimental data...