AI Medical Compendium Journal:
Nucleic acids research

Showing 61 to 70 of 228 articles

m6ACali: machine learning-powered calibration for accurate m6A detection in MeRIP-Seq.

Nucleic acids research
We present m6ACali, a novel machine-learning framework aimed at enhancing the accuracy of N6-methyladenosine (m6A) epitranscriptome profiling by reducing the impact of non-specific antibody enrichment in MeRIP-Seq. The calibration model serves as a g...

Prediction of DNA i-motifs via machine learning.

Nucleic acids research
i-Motifs (iMs), are secondary structures formed in cytosine-rich DNA sequences and are involved in multiple functions in the genome. Although putative iM forming sequences are widely distributed in the human genome, the folding status and strength of...

EquiPNAS: improved protein-nucleic acid binding site prediction using protein-language-model-informed equivariant deep graph neural networks.

Nucleic acids research
Protein language models (pLMs) trained on a large corpus of protein sequences have shown unprecedented scalability and broad generalizability in a wide range of predictive modeling tasks, but their power has not yet been harnessed for predicting prot...

Language model-based B cell receptor sequence embeddings can effectively encode receptor specificity.

Nucleic acids research
High throughput sequencing of B cell receptors (BCRs) is increasingly applied to study the immense diversity of antibodies. Learning biologically meaningful embeddings of BCR sequences is beneficial for predictive modeling. Several embedding methods ...

Multiple sequence alignment-based RNA language model and its application to structural inference.

Nucleic acids research
Compared with proteins, DNA and RNA are more difficult languages to interpret because four-letter coded DNA/RNA sequences have less information content than 20-letter coded protein sequences. While BERT (Bidirectional Encoder Representations from Tra...

CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions.

Nucleic acids research
Machine Learning-based scoring and classification of genetic variants aids the assessment of clinical findings and is employed to prioritize variants in diverse genetic studies and analyses. Combined Annotation-Dependent Depletion (CADD) is one of th...

Plant Reactome Knowledgebase: empowering plant pathway exploration and OMICS data analysis.

Nucleic acids research
Plant Reactome (https://plantreactome.gramene.org) is a freely accessible, comprehensive plant pathway knowledgebase. It provides curated reference pathways from rice (Oryza sativa) and gene-orthology-based pathway projections to 129 additional speci...

The Human Phenotype Ontology in 2024: phenotypes around the world.

Nucleic acids research
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similar...

The DO-KB Knowledgebase: a 20-year journey developing the disease open science ecosystem.

Nucleic acids research
In 2003, the Human Disease Ontology (DO, https://disease-ontology.org/) was established at Northwestern University. In the intervening 20 years, the DO has expanded to become a highly-utilized disease knowledge resource. Serving as the nomenclature a...

DrugBank 6.0: the DrugBank Knowledgebase for 2024.

Nucleic acids research
First released in 2006, DrugBank (https://go.drugbank.com) has grown to become the 'gold standard' knowledge resource for drug, drug-target and related pharmaceutical information. DrugBank is widely used across many diverse biomedical research and cl...