A roadmap for multi-omics data integration using deep learning

M Kang, E Ko, TB Mersha - Briefings in Bioinformatics, 2022 - academic.oup.com
High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …

Incorporating machine learning into established bioinformatics frameworks

N Auslander, AB Gussow, EV Koonin - International journal of molecular …, 2021 - mdpi.com
The exponential growth of biomedical data in recent years has urged the application of
numerous machine learning techniques to address emerging problems in biology and …

Trends in persuasive technologies for physical activity and sedentary behavior: a systematic review

N Aldenaini, F Alqahtani, R Orji… - Frontiers in artificial …, 2020 - frontiersin.org
Persuasive technology (PT) is increasingly being used in the health and wellness domain to
motivate and assist users with different lifestyles and behavioral health issues to change …

A Monte Carlo evaluation of weighted community detection algorithms

KM Gates, T Henry, D Steinley, DA Fair - Frontiers in neuroinformatics, 2016 - frontiersin.org
The past decade has been marked with a proliferation of community detection algorithms
that aim to organize nodes (eg, individuals, brain regions, variables) into modular structures …

Automatic classification of colour fundus images for prediction eye disease types based on hybrid features

A Shamsan, EM Senan, HSA Shatnawi - Diagnostics, 2023 - mdpi.com
Early detection of eye diseases is the only solution to receive timely treatment and prevent
blindness. Colour fundus photography (CFP) is an effective fundus examination technique …

Computer Generated Realistic Interstellar Icy Grain Models: Physicochemical Properties and Interaction with NH3

A Germain, L Tinacci, S Pantaleone… - ACS Earth and Space …, 2022 - ACS Publications
Interstellar grains are composed by a rocky core (usually amorphous silicates) covered by
an icy mantle, the most abundant molecule being H2O followed by CO, CO2, NH3, and also …

A Visual Designer of Layer‐wise Relevance Propagation Models

X Huang, S Jamonnak, Y Zhao… - Computer Graphics …, 2021 - Wiley Online Library
Abstract Layer‐wise Relevance Propagation (LRP) is an emerging and widely‐used method
for interpreting the prediction results of convolutional neural networks (CNN). LRP …

Detection of autism spectrum disorder using graph representation learning algorithms and deep neural network, based on fMRI signals

A Yousefian, F Shayegh, Z Maleki - Frontiers in Systems …, 2023 - frontiersin.org
Introduction Can we apply graph representation learning algorithms to identify autism
spectrum disorder (ASD) patients within a large brain imaging dataset? ASD is mainly …

Detection and analysis of heartbeats in seismocardiogram signals

N Mora, F Cocconcelli, G Matrella, P Ciampolini - Sensors, 2020 - mdpi.com
This paper presents an unsupervised methodology to analyze SeismoCardioGram (SCG)
signals. Starting from raw accelerometric data, heartbeat complexes are extracted and …

Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks

E Díaz-Santiago, AA Moya-García… - Frontiers in …, 2025 - frontiersin.org
Introduction Most drugs fail during development and there is a clear and unmet need for
approaches to better understand mechanistically how drugs exert both their intended and …