Understanding artificial intelligence and predictive analytics: a clinically focused review of machine learning techniques

B Cho, E Geng, V Arvind, AA Valliani, JE Tang… - JBJS …, 2022 - journals.lww.com
Understanding Artificial Intelligence and Predictive Analyti... : JBJS Reviews Understanding
Artificial Intelligence and Predictive Analytics: A Clinically Focused Review of Machine …

Netpro2vec: a graph embedding framework for biomedical applications

I Manipur, M Manzo, I Granata… - IEEE/ACM …, 2021 - ieeexplore.ieee.org
The ever-increasing importance of structured data in different applications, especially in the
biomedical field, has driven the need for reducing its complexity through projections into a …

Unraveling the glycosphingolipid metabolism by leveraging transcriptome-weighted network analysis on neuroblastic tumors

A Ustjanzew, AS Nedwed, R Sandhoff, J Faber… - Cancer & …, 2024 - Springer
Abstract Background Glycosphingolipids (GSLs) are membrane lipids composed of a
ceramide backbone linked to a glycan moiety. Ganglioside biosynthesis is a part of the GSL …

Learning from metabolic networks: Current trends and future directions for precision medicine

I Granata, M Manzo, A Kusumastuti… - Current Medicinal …, 2021 - ingentaconnect.com
Background: Systems biology and network modeling represent, nowadays, the hallmark
approaches for the development of predictive and targeted-treatment based precision …

Representing ensembles of networks for fuzzy cluster analysis: a case study

I Bombelli, I Manipur, MR Guarracino… - Data Mining and …, 2024 - Springer
As the statistical analysis of networks finds application in an increasing number of
disciplines, novel methodologies are needed to handle such complexity. In particular, cluster …

Adversarial attacks on graph-level embedding methods: A case study

M Giordano, L Maddalena, M Manzo… - Annals of Mathematics …, 2023 - Springer
As the number of graph-level embedding techniques increases at an unprecedented speed,
questions arise about their behavior and performance when training data undergo …

Whole-graph embedding and adversarial attacks for life sciences

L Maddalena, M Giordano, M Manzo… - … on Mathematical and …, 2021 - Springer
Networks provide a suitable model for many scientific and technological problems that
require the representation of complex entities and their relations. Life sciences applications …

TumorMet: a repository of tumor metabolic networks derived from context-specific genome-scale metabolic models

I Granata, I Manipur, M Giordano, L Maddalena… - Scientific Data, 2022 - nature.com
Studies about the metabolic alterations during tumorigenesis have increased our knowledge
of the underlying mechanisms and consequences, which are important for diagnostic and …

On whole-graph embedding techniques

L Maddalena, I Manipur, M Manzo… - … : Chaos and Control in …, 2021 - Springer
Networks provide suitable representative models in many applications, ranging from social
to life sciences. Such representations are able to capture interactions and dependencies …

Novel Data Science Methodologies for Essential Genes Identification Based on Network Analysis

M Manzo, M Giordano, L Maddalena… - Data Science in …, 2023 - Springer
Essential genes (EGs) are fundamental for the growth and survival of a cell or an organism.
Identifying EGs is an important issue in many areas of biomedical research, such as …