Pre‐Training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding
Sign Up to like & getrecommendations! Published in 2022 at "Advanced Science"
DOI: 10.1002/advs.202203796
Abstract: The latest biological findings observe that the motionless “lock‐and‐key” theory is not generally applicable and that changes in atomic sites and binding pose can provide important information for understanding drug binding. However, the computational expenditure… read more here.
Keywords: equivariant graph; graph matching; matching networks; drug binding ... See more keywords
Finding a good initial configuration of parameters for restricted Boltzmann machine pre-training
Sign Up to like & getrecommendations! Published in 2017 at "Soft Computing"
DOI: 10.1007/s00500-016-2205-z
Abstract: Restricted Boltzmann machines (RBMs) have been successfully applied in unsupervised learning and image density-based modeling. The aim of the pre-training step for RBMs is to discover an unknown stationary distribution based on the sample data… read more here.
Keywords: good initial; restricted boltzmann; pre training; pre ... See more keywords
Multimodal image encoding pre-training for diabetic retinopathy grading
Sign Up to like & getrecommendations! Published in 2022 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2022.105302
Abstract: Diabetic retinopathy is an increasingly prevalent eye disorder that can lead to severe vision impairment. The severity grading of the disease using retinal images is key to provide an adequate treatment. However, in order to… read more here.
Keywords: grading diabetic; image; pre training; diabetic retinopathy ... See more keywords
Data-driven strength and conditioning, and technical training programs for goalkeeper's diving save in football.
Sign Up to like & getrecommendations! Published in 2022 at "Sports biomechanics"
DOI: 10.1080/14763141.2022.2099966
Abstract: The goal of this study was to evaluate the technical and physical adaptations to a data-driven 12-weeks training programs that incorporated recent findings from biomechanical studies on the diving save. Three-dimensional kinematics and kinetics were… read more here.
Keywords: training programs; diving save; post training; training ... See more keywords
Non-invasive blood pressure estimation combining deep neural networks with pre-training and partial fine-tuning
Sign Up to like & getrecommendations! Published in 2022 at "Physiological Measurement"
DOI: 10.1088/1361-6579/ac9d7f
Abstract: Objective. Daily blood pressure (BP) monitoring is essential since BP levels can reflect the functions of heart pumping and vasoconstriction. Although various neural network-based BP estimate approaches have been proposed, they have certain practical shortcomings,… read more here.
Keywords: pre training; non invasive; fine tuning; estimation ... See more keywords
SIFLoc: a self-supervised pre-training method for enhancing the recognition of protein subcellular localization in immunofluorescence microscopic images
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbab605
Abstract: With the rapid growth of high-resolution microscopy imaging data, revealing the subcellular map of human proteins has become a central task in the spatial proteome. The cell atlas of the Human Protein Atlas (HPA) provides… read more here.
Keywords: self supervised; subcellular localization; microscopic images; pre training ... See more keywords
Knowledge-based BERT: a method to extract molecular features like computational chemists
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac131
Abstract: Molecular property prediction models based on machine learning algorithms have become important tools to triage unpromising lead molecules in the early stages of drug discovery. Compared with the mainstream descriptor- and graph-based methods for molecular… read more here.
Keywords: extract molecular; method; molecular features; molecular property ... See more keywords
SPRoBERTa: protein embedding learning with local fragment modeling
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac401
Abstract: Well understanding protein function and structure in computational biology helps in the understanding of human beings. To face the limited proteins that are annotated structurally and functionally, the scientific community embraces the self-supervised pre-training methods… read more here.
Keywords: embedding learning; local fragment; prediction; protein ... See more keywords
Pre-training graph neural networks for link prediction in biomedical networks
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac100
Abstract: MOTIVATION Graphs or networks are widely utilized to model the interactions between different entities (e.g., proteins, drugs, etc) for biomedical applications. Predicting potential interactions/links in biomedical networks is important for understanding the pathological mechanisms of… read more here.
Keywords: neural networks; biomedical networks; prediction; graph neural ... See more keywords
SPAKT: A Self-Supervised Pre-TrAining Method for Knowledge Tracing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3187987
Abstract: Knowledge tracing (KT) is the core task of computer-aided education systems, and it aims at predicting whether a student can answer the next exercise (i.e., question) correctly based on his/her historical answer records. In recent… read more here.
Keywords: self supervised; knowledge tracing; spakt self; pre training ... See more keywords
SSCLNet: A Self-Supervised Contrastive Loss-Based Pre-Trained Network for Brain MRI Classification
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3237542
Abstract: Brain magnetic resonance images (MRI) convey vital information for making diagnostic decisions and are widely used to detect brain tumors. This research proposes a self-supervised pre-training method based on feature representation learning through contrastive loss… read more here.
Keywords: brain; contrastive loss; loss based; self supervised ... See more keywords