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Quantifying uncertainty in protein representations across models and tasks

Biomolecular embeddings serve as efficient representations of sequence and structure, enabling tasks such as similarity searches, structure and function prediction and estimation of biophysical properties. However, relying on embeddings without …

16S rRNA k-mer composition encodes microbial functional potential

16S rRNA amplicon sequencing is widely used for microbiome profiling, but most methods rely on reference databases of characterized organisms, limiting its accuracy in function prediction for underrepresented environments. We discovered that 16S rRNA …

From Awareness to ACTion Study: Improving Human Papillomavirus Knowledge, Screening, and Vaccine Uptake in Adolescent-Mother Pairs in the HOMINY study in Nigeria

Introduction Persistent infection with high-risk Human Papillomavirus (hr-HPV) in women is a leading cause of cervical cancer, and its co-infection among people living with HIV (PLHIV) increases the risk of HPV-associated cancer, including …

Oral HPV and Dental Profiles in Mothers and Youth with or without HIV

Background People living with HIV (PLWH) are more susceptible to persistent human papilloma virus (HPV) infection; however, data regarding oral HPV burden among youth with or without perinatal HIV exposure or infection in sub-Saharan Africa remain …

Deciphering enzymatic potential in metagenomic reads through DNA language models

Microbial communities drive essential global processes, yet much of their functional potential remains unexplored. Metagenomics stands to elucidate this microbial “dark matter” by directly sequencing the microbial community DNA from environmental …

Functional profiling of the sequence stockpile: a protein pair-based assessment of in silico prediction tools

In silico functional annotation of proteins is crucial to narrowing the sequencing-accelerated gap in our understanding of protein activities. Numerous function annotation methods exist, and their ranks have been growing, particularly so with the …

3.1 Artificial Intelligence and the Future of Biotechnology

Integration of artificial intelligence (AI) and biotechnology (AIxBio) creates revolutionary opportunities for progress in advancing the bioeconomy and addressing health concerns. AI advances promise to greatly accelerate beneficial biological …

An interdisciplinary perspective of the built-environment microbiome

The built environment provides an excellent setting for interdisciplinary research on the dynamics of microbial communities. The system is simplified compared to many natural settings, and to some extent the entire environment can be manipulated, …

Biological molecular function: methods and benchmarks for finding function in biological dark matter

The accurate determination of biological molecular function remains one of the most significant challenges in computational biology, with vast areas of biological “dark matter” persisting in microbiomes, viruses, and unexplored sequence space. To …

Editorial overview: Protein folding and binding-With a little help from AI.