AIMC Topic: Software

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Protein-protein interaction site prediction through combining local and global features with deep neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interactions (PPIs) play important roles in many biological processes. Conventional biological experiments for identifying PPI sites are costly and time-consuming. Thus, many computational approaches have been proposed to ...

Graph embedding on biomedical networks: methods, applications and evaluations.

Bioinformatics (Oxford, England)
MOTIVATION: Graph embedding learning that aims to automatically learn low-dimensional node representations, has drawn increasing attention in recent years. To date, most recent graph embedding methods are evaluated on social and information networks ...

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites.

Bioinformatics (Oxford, England)
MOTIVATION: Proteases are enzymes that cleave target substrate proteins by catalyzing the hydrolysis of peptide bonds between specific amino acids. While the functional proteolysis regulated by proteases plays a central role in the 'life and death' c...

Applying citizen science to gene, drug and disease relationship extraction from biomedical abstracts.

Bioinformatics (Oxford, England)
MOTIVATION: Biomedical literature is growing at a rate that outpaces our ability to harness the knowledge contained therein. To mine valuable inferences from the large volume of literature, many researchers use information extraction algorithms to ha...

BioBERT: a pre-trained biomedical language representation model for biomedical text mining.

Bioinformatics (Oxford, England)
MOTIVATION: Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained p...

Artificial intelligence deciphers codes for color and odor perceptions based on large-scale chemoinformatic data.

GigaScience
BACKGROUND: Color vision is the ability to detect, distinguish, and analyze the wavelength distributions of light independent of the total intensity. It mediates the interaction between an organism and its environment from multiple important aspects....

Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.

Indian journal of ophthalmology
PURPOSE: An observational study to assess the sensitivity and specificity of the Medios smartphone-based offline deep learning artificial intelligence (AI) software to detect diabetic retinopathy (DR) compared with the image diagnosis of ophthalmolog...

BioNorm: deep learning-based event normalization for the curation of reaction databases.

Bioinformatics (Oxford, England)
MOTIVATION: A biochemical reaction, bio-event, depicts the relationships between participating entities. Current text mining research has been focusing on identifying bio-events from scientific literature. However, rare efforts have been dedicated to...

The neXtProt knowledgebase in 2020: data, tools and usability improvements.

Nucleic acids research
The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describ...

BiGG Models 2020: multi-strain genome-scale models and expansion across the phylogenetic tree.

Nucleic acids research
The BiGG Models knowledge base (http://bigg.ucsd.edu) is a centralized repository for high-quality genome-scale metabolic models. For the past 12 years, the website has allowed users to browse and search metabolic models. Within this update, we detai...