AIMC Topic: Metagenome

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Functional archetypes in the human gut microbiome reveal metabolic diversity, stability, and influence disease-associated signatures.

Microbiome
BACKGROUND: Understanding the functional diversity of the gut microbiome is critical for elucidating its roles in human health and disease. While traditional approaches focus on taxonomic composition, functional configurations of the microbiome remai...

Machine learning-guided discovery of thermophilic carbonic anhydrases from environmental metagenomes.

Scientific reports
Thermophilic carbonic anhydrases (CAs) are promising biocatalysts for carbon capture utilization and storage (CCUS) due to their stability and efficiency at elevated temperatures. This study presents a machine learning (ML)-guided approach to discove...

Enhancing peptide identification in metaproteomics through curriculum learning in deep learning.

Nature communications
Metaproteomics offers a powerful window into the active functions of microbial communities, but accurately identifying peptides remains challenging due to the size and incompleteness of protein databases derived from metagenomes. These databases ofte...

Harnessing machine learning for metagenomic data analysis: trends and applications.

mSystems
Metagenomic sequencing has revolutionized our understanding of microbial ecosystems by enabling high-resolution profiling of microbes across diverse environments. However, the resulting data are high-dimensional, sparse, and noisy, posing challenges ...

Global wastewater microbiome reveals core bacterial community and viral diversity with regional antibiotic resistance patterns.

mSystems
Municipal wastewater treatment plants (WWTPs) serve as global repositories for diverse and dynamic microbial communities, reflecting the complex interplay of human activities, environmental conditions, and public health challenges. Despite their impo...

Environmental adaptations in metagenomes revealed by deep learning.

BMC biology
BACKGROUND: Deep learning has emerged as a powerful tool in the analysis of biological data, including the analysis of large metagenome data. However, its application remains limited due to high computational costs, model complexity, and difficulty e...

Extensive novel diversity and phenotypic associations in the dromedary camel microbiome are revealed through deep metagenomics and machine learning.

PloS one
The dromedary camel, also known as one-humped camel or Arabian camel, is iconic and economically important to Arabian society. Its contemporary importance in commerce and transportation, along with the historical and modern use of its milk and meat p...

Machine learning-based meta-analysis reveals gut microbiome alterations associated with Parkinson's disease.

Nature communications
There is strong interest in using the gut microbiome for Parkinson's disease (PD) diagnosis and treatment. However, a consensus on PD-associated microbiome features and a multi-study assessment of their diagnostic value is lacking. Here, we present a...

Exploring deep learning in phage discovery and characterization.

Virology
Bacteriophages, or bacterial viruses, play diverse ecological roles by shaping bacterial populations and also hold significant biotechnological and medical potential, including the treatment of infections caused by multidrug-resistant bacteria. The d...

Microbiome and fragmentation pattern of blood cell-free DNA and fecal metagenome enhance colorectal cancer micro-dysbiosis and diagnosis analysis: a proof-of-concept study.

mSystems
Colorectal cancer (CRC) is the third most common cancer, and it can be prevented by performing early screening. As a hallmark of cancer, the human microbiome plays important roles in the occurrence and development of CRC. Recently, the blood microbio...