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A review of mathematical representations of biomolecular data
Recently, machine learning (ML) has established itself in various worldwide benchmarking
competitions in computational biology, including Critical Assessment of Structure Prediction …
competitions in computational biology, including Critical Assessment of Structure Prediction …
TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions
Although deep learning approaches have had tremendous success in image, video and
audio processing, computer vision, and speech recognition, their applications to three …
audio processing, computer vision, and speech recognition, their applications to three …
Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening
This work introduces a number of algebraic topology approaches, including multi-
component persistent homology, multi-level persistent homology, and electrostatic …
component persistent homology, multi-level persistent homology, and electrostatic …
Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges
Advanced mathematics, such as multiscale weighted colored subgraph and element specific
persistent homology, and machine learning including deep neural networks were integrated …
persistent homology, and machine learning including deep neural networks were integrated …
Quantitative toxicity prediction using topology based multitask deep neural networks
The understanding of toxicity is of paramount importance to human health and
environmental protection. Quantitative toxicity analysis has become a new standard in the …
environmental protection. Quantitative toxicity analysis has become a new standard in the …
MathDL: mathematical deep learning for D3R Grand Challenge 4
We present the performances of our mathematical deep learning (MathDL) models for D3R
Grand Challenge 4 (GC4). This challenge involves pose prediction, affinity ranking, and free …
Grand Challenge 4 (GC4). This challenge involves pose prediction, affinity ranking, and free …
Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology
Motivation Site directed mutagenesis is widely used to understand the structure and function
of biomolecules. Computational prediction of mutation impacts on protein stability offers a …
of biomolecules. Computational prediction of mutation impacts on protein stability offers a …
Persistent spectral based ensemble learning (PerSpect-EL) for protein–protein binding affinity prediction
Protein–protein interactions (PPIs) play a significant role in nearly all cellular and biological
activities. Data-driven machine learning models have demonstrated great power in PPIs …
activities. Data-driven machine learning models have demonstrated great power in PPIs …
Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation
Protein mutations can significantly influence protein solubility, which results in altered
protein functions and leads to various diseases. Despite tremendous effort, machine …
protein functions and leads to various diseases. Despite tremendous effort, machine …
A review of geometric, topological and graph theory apparatuses for the modeling and analysis of biomolecular data
Geometric, topological and graph theory modeling and analysis of biomolecules are of
essential importance in the conceptualization of molecular structure, function, dynamics, and …
essential importance in the conceptualization of molecular structure, function, dynamics, and …