AIMC Topic: Neural Networks, Computer

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Adopting improved Adam optimizer to train dendritic neuron model for water quality prediction.

Mathematical biosciences and engineering : MBE
As one of continuous concern all over the world, the problem of water quality may cause diseases and poisoning and even endanger people's lives. Therefore, the prediction of water quality is of great significance to the efficient management of water ...

DeepFormer: a hybrid network based on convolutional neural network and flow-attention mechanism for identifying the function of DNA sequences.

Briefings in bioinformatics
Identifying the function of DNA sequences accurately is an essential and challenging task in the genomic field. Until now, deep learning has been widely used in the functional analysis of DNA sequences, including DeepSEA, DanQ, DeepATT and TBiNet. Ho...

Identification of significant gene expression changes in multiple perturbation experiments using knockoffs.

Briefings in bioinformatics
Large-scale multiple perturbation experiments have the potential to reveal a more detailed understanding of the molecular pathways that respond to genetic and environmental changes. A key question in these studies is which gene expression changes are...

PPICT: an integrated deep neural network for predicting inter-protein PTM cross-talk.

Briefings in bioinformatics
Post-translational modifications (PTMs) fine-tune various signaling pathways not only by the modification of a single residue, but also by the interplay of different modifications on residue pairs within or between proteins, defined as PTM cross-talk...

Identification of metal ion-binding sites in RNA structures using deep learning method.

Briefings in bioinformatics
Metal ion is an indispensable factor for the proper folding, structural stability and functioning of RNA molecules. However, it is very difficult for experimental methods to detect them in RNAs. With the increase of experimentally resolved RNA struct...

Improved drug response prediction by drug target data integration via network-based profiling.

Briefings in bioinformatics
Drug response prediction (DRP) is important for precision medicine to predict how a patient would react to a drug before administration. Existing studies take the cell line transcriptome data, and the chemical structure of drugs as input and predict ...

Cooperation of local features and global representations by a dual-branch network for transcription factor binding sites prediction.

Briefings in bioinformatics
Interactions between DNA and transcription factors (TFs) play an essential role in understanding transcriptional regulation mechanisms and gene expression. Due to the large accumulation of training data and low expense, deep learning methods have sho...

High-accuracy protein model quality assessment using attention graph neural networks.

Briefings in bioinformatics
Great improvement has been brought to protein tertiary structure prediction through deep learning. It is important but very challenging to accurately rank and score decoy structures predicted by different models. CASP14 results show that existing qua...

Identification of species-specific RNA N6-methyladinosine modification sites from RNA sequences.

Briefings in bioinformatics
N6-methyladinosine (m6A) modification is the most abundant co-transcriptional modification in eukaryotic RNA and plays important roles in cellular regulation. Traditional high-throughput sequencing experiments used to explore functional mechanisms ar...

COVID-19 disease identification network based on weakly supervised feature selection.

Mathematical biosciences and engineering : MBE
The coronavirus disease 2019 (COVID-19) outbreak has resulted in countless infections and deaths worldwide, posing increasing challenges for the health care system. The use of artificial intelligence to assist in diagnosis not only had a high accurac...