AIMC Topic: Molecular Sequence Annotation
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ISPRED-SEQ: Deep Neural Networks and Embeddings for Predicting Interaction Sites in Protein Sequences.
Journal of molecular biology
Jan 13, 2023
The knowledge of protein-protein interaction sites (PPIs) is crucial for protein functional annotation. Here we address the problem focusing on the prediction of putative PPIs considering as input protein sequences. The issue is important given the h...
DeepPlnc: Bi-modal deep learning for highly accurate plant lncRNA discovery.
Genomics
Aug 2, 2022
We present here a bi-modal CNN based deep-learning system, DeepPlnc, to identify plant lncRNAs with high accuracy while using sequence and structural properties. Unlike most of the existing software, it works accurately even in conditions with ambigu...
PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods.
Computers in biology and medicine
Mar 28, 2022
Bioinformatic annotation of protein function is essential but extremely sophisticated, which asks for extensive efforts to develop effective prediction method. However, the existing methods tend to amplify the representativeness of the families with ...
Using deep learning to annotate the protein universe.
Nature biotechnology
Feb 21, 2022
Understanding the relationship between amino acid sequence and protein function is a long-standing challenge with far-reaching scientific and translational implications. State-of-the-art alignment-based techniques cannot predict function for one-thir...
Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset.
Nature communications
Dec 15, 2021
To accelerate cancer research that correlates biomarkers with clinical endpoints, methods are needed to ascertain outcomes from electronic health records at scale. Here, we train deep natural language processing (NLP) models to extract outcomes for p...
A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2021
Knowledge of protein functions plays an important role in biology and medicine. With the rapid development of high-throughput technologies, a huge number of proteins have been discovered. However, there are a great number of proteins without function...
An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila.
Genome biology
Nov 8, 2021
BACKGROUND: Enhancers are non-coding regions of the genome that control the activity of target genes. Recent efforts to identify active enhancers experimentally and in silico have proven effective. While these tools can predict the locations of enhan...
Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO).
PLoS computational biology
Oct 28, 2021
Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying ...
PIC-Me: paralogs and isoforms classifier based on machine-learning approaches.
BMC bioinformatics
Oct 21, 2021
BACKGROUND: Paralogs formed through gene duplication and isoforms formed through alternative splicing have been important processes for increasing protein diversity and maintaining cellular homeostasis. Despite their recognized importance and the adv...
A GO catalogue of human DNA-binding transcription factors.
Biochimica et biophysica acta. Gene regulatory mechanisms
Oct 18, 2021
To control gene transcription, DNA-binding transcription factors recognise specific sequence motifs in gene regulatory regions. A complete and reliable GO annotation of all DNA-binding transcription factors is key to investigating the delicate balanc...
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