AIMC Topic: Neural Networks, Computer

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Assessing the impacts of climate change on streamflow dynamics: A machine learning perspective.

Water science and technology : a journal of the International Association on Water Pollution Research
This study investigates changes in river flow patterns, in the Hunza Basin, Pakistan, attributed to climate change. Given the anticipated rise in extreme weather events, accurate streamflow predictions are increasingly vital. We assess three machine ...

ReGeNNe: genetic pathway-based deep neural network using canonical correlation regularizer for disease prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Common human diseases result from the interplay of genes and their biologically associated pathways. Genetic pathway analyses provide more biological insight as compared to conventional gene-based analysis. In this article, we propose a f...

Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs.

Bioinformatics (Oxford, England)
MOTIVATION: Dynamical properties of biochemical pathways (BPs) help in understanding the functioning of living cells. Their in silico assessment requires simulating a dynamical system with a large number of parameters such as kinetic constants and sp...

SSLpheno: a self-supervised learning approach for gene-phenotype association prediction using protein-protein interactions and gene ontology data.

Bioinformatics (Oxford, England)
MOTIVATION: Medical genomics faces significant challenges in interpreting disease phenotype and genetic heterogeneity. Despite the establishment of standardized disease phenotype databases, computational methods for predicting gene-phenotype associat...

PROSTATA: a framework for protein stability assessment using transformers.

Bioinformatics (Oxford, England)
MOTIVATION: Accurate prediction of change in protein stability due to point mutations is an attractive goal that remains unachieved. Despite the high interest in this area, little consideration has been given to the transformer architecture, which is...

Automated exploitation of deep learning for cancer patient stratification across multiple types.

Bioinformatics (Oxford, England)
MOTIVATION: Recent frameworks based on deep learning have been developed to identify cancer subtypes from high-throughput gene expression profiles. Unfortunately, the performance of deep learning is highly dependent on its neural network architecture...

Prediction of Central Visual Field Measures From Macular OCT Volume Scans With Deep Learning.

Translational vision science & technology
PURPOSE: Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL).

THPLM: a sequence-based deep learning framework for protein stability changes prediction upon point variations using pretrained protein language model.

Bioinformatics (Oxford, England)
MOTIVATION: Quantitative determination of protein thermodynamic stability is a critical step in protein and drug design. Reliable prediction of protein stability changes caused by point variations contributes to developing-related fields. Over the pa...