AIMC Topic: Computational Biology
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VacSol-ML(ESKAPE) Machine learning empowering vaccine antigen prediction for ESKAPE pathogens.
Vaccine
Aug 9, 2024
The ESKAPE family, comprising Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., poses a significant global threat due to their heightened virulence and extensiv...
Guiding questions to avoid data leakage in biological machine learning applications.
Nature methods
Aug 9, 2024
Machine learning methods for extracting patterns from high-dimensional data are very important in the biological sciences. However, in certain cases, real-world applications cannot confirm the reported prediction performance. One of the main reasons ...
Language models for biological research: a primer.
Nature methods
Aug 9, 2024
Language models are playing an increasingly important role in many areas of artificial intelligence (AI) and computational biology. In this primer, we discuss the ways in which language models, both those based on natural language and those based on ...
Applying interpretable machine learning in computational biology-pitfalls, recommendations and opportunities for new developments.
Nature methods
Aug 9, 2024
Recent advances in machine learning have enabled the development of next-generation predictive models for complex computational biology problems, thereby spurring the use of interpretable machine learning (IML) to unveil biological insights. However,...
A Secure High-Order Gene Interaction Detection Algorithm Based on Deep Neural Network.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 9, 2024
Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model is crucial for detecting complex disease gene-type and predicting pathogenic genes of various disorders. We present a novel framework for high-order ge...
Artificial intelligence methods available for cancer research.
Frontiers of medicine
Aug 8, 2024
Cancer is a heterogeneous and multifaceted disease with a significant global footprint. Despite substantial technological advancements for battling cancer, early diagnosis and selection of effective treatment remains a challenge. With the convenience...
Convolutional neural networks can identify brain interactions involved in decoding spatial auditory attention.
PLoS computational biology
Aug 8, 2024
Human listeners have the ability to direct their attention to a single speaker in a multi-talker environment. The neural correlates of selective attention can be decoded from a single trial of electroencephalography (EEG) data. In this study, leverag...
DFML: Dynamic Federated Meta-Learning for Rare Disease Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Millions of patients suffer from rare diseases around the world. However, the samples of rare diseases are much smaller than those of common diseases. Hospitals are usually reluctant to share patient information for data fusion due to the sensitivity...
Hierarchical Graph Capsule Networks for Molecular Function Classification With Disentangled Representations.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
In biochemistry, graph structures have been widely used for modeling compounds, proteins, functional interactions, etc. A common task that divides these graphs into different categories, known as graph classification, highly relies on the quality of ...
Graph Embedded Ensemble Deep Randomized Network for Diagnosis of Alzheimer's Disease.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Randomized shallow/deep neural networks with closed form solution avoid the shortcomings that exist in the back propagation (BP) based trained neural networks. Ensemble deep random vector functional link (edRVFL) network utilize the strength of two g...
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