AIMC Topic: Software

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Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease.

European heart journal
The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such AI-based prediction model tools and software in cardiovascular patient care, the cardiovascular rese...

Braitenberg Vehicles as Developmental Neurosimulation.

Artificial life
Connecting brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is pr...

[Development of Nasal Continuum Minimally Invasive Surgical Robot System].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
In order to improve the operation difficulties in the narrow space of the nasal maxillary sinus, the nasal continuum minimally invasive surgical robot system is designed. The ball-and-socket joints and NiTiNol tubes are used as the main body of the c...

STNN-DDI: a Substructure-aware Tensor Neural Network to predict Drug-Drug Interactions.

Briefings in bioinformatics
Computational prediction of multiple-type drug-drug interaction (DDI) helps reduce unexpected side effects in poly-drug treatments. Although existing computational approaches achieve inspiring results, they ignore to study which local structures of d...

NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning.

Nucleic acids research
Recent advances in machine learning and natural language processing have made it possible to profoundly advance our ability to accurately predict protein structures and their functions. While such improvements are significantly impacting the fields o...

PRECOGx: exploring GPCR signaling mechanisms with deep protein representations.

Nucleic acids research
In this study we show that protein language models can encode structural and functional information of GPCR sequences that can be used to predict their signaling and functional repertoire. We used the ESM1b protein embeddings as features and the bind...

CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning.

Nucleic acids research
Recent advances in protein structural modelling have enabled the accurate prediction of the holo 3D structures of almost any protein, however protein function is intrinsically linked to the interactions it makes. While a number of computational appro...

DLEB: a web application for building deep learning models in biological research.

Nucleic acids research
Deep learning has been applied for solving many biological problems, and it has shown outstanding performance. Applying deep learning in research requires knowledge of deep learning theories and programming skills, but researchers have developed dive...

DEMO2: Assemble multi-domain protein structures by coupling analogous template alignments with deep-learning inter-domain restraint prediction.

Nucleic acids research
Most proteins in nature contain multiple folding units (or domains). The revolutionary success of AlphaFold2 in single-domain structure prediction showed potential to extend deep-learning techniques for multi-domain structure modeling. This work pres...