[HTML][HTML] Liquid biopsies and cancer omics

I Amelio, R Bertolo, P Bove, OC Buonomo… - Cell Death …, 2020 - nature.com
The development of the sequencing technologies allowed the generation of huge amounts
of molecular data from a single cancer specimen, allowing the clinical oncology to enter the …

[HTML][HTML] Cancer predictive studies

I Amelio, R Bertolo, P Bove, E Candi, M Chiocchi… - Biology direct, 2020 - Springer
The identification of individual or clusters of predictive genetic alterations might help in
defining the outcome of cancer treatment, allowing for the stratification of patients into …

Identification of drug-disease associations by using multiple drug and disease networks

Y Yang, L Chen - Current Bioinformatics, 2022 - ingentaconnect.com
Background: Drug repositioning is a new research area in drug development. It aims to
discover novel therapeutic uses of existing drugs. It could accelerate the process of …

Predicting drug side effects with compact integration of heterogeneous networks

X Zhao, L Chen, ZH Guo, T Liu - Current Bioinformatics, 2019 - ingentaconnect.com
Background: The side effects of drugs are not only harmful to humans but also the major
reasons for withdrawing approved drugs, bringing greater risks for pharmaceutical …

[HTML][HTML] iMPTCE-Hnetwork: a multilabel classifier for identifying metabolic pathway types of chemicals and enzymes with a heterogeneous network

Y Zhu, B Hu, L Chen, Q Dai - Computational and Mathematical …, 2021 - hindawi.com
Metabolic pathway is an important type of biological pathways. It produces essential
molecules and energies to maintain the life of living organisms. Each metabolic pathway …

[HTML][HTML] A novel framework for horizontal and vertical data integration in cancer studies with application to survival time prediction models

I Mihaylov, M Kańduła, M Krachunov, D Vassilev - Biology direct, 2019 - Springer
Background Recently high-throughput technologies have been massively used alongside
clinical tests to study various types of cancer. Data generated in such large-scale studies are …

[HTML][HTML] Network-based integration of multi-omics data for clinical outcome prediction in neuroblastoma

C Wang, W Lue, R Kaalia, P Kumar, JC Rajapakse - Scientific Reports, 2022 - nature.com
Multi-omics data are increasingly being gathered for investigations of complex diseases
such as cancer. However, high dimensionality, small sample size, and heterogeneity of …

Drug target group prediction with multiple drug networks

J Che, L Chen, ZH Guo, S Wang - Combinatorial Chemistry & …, 2020 - ingentaconnect.com
Background: Identification of drug-target interaction is essential in drug discovery. It is
beneficial to predict unexpected therapeutic or adverse side effects of drugs. To date …

[HTML][HTML] A deep neural network approach to predicting clinical outcomes of neuroblastoma patients

LC Tranchevent, F Azuaje, JC Rajapakse - BMC medical genomics, 2019 - Springer
Background The availability of high-throughput omics datasets from large patient cohorts
has allowed the development of methods that aim at predicting patient clinical outcomes …

[HTML][HTML] The ZNF750–RAC1 axis as potential prognostic factor for breast cancer

A Butera, M Cassandri, F Rugolo, M Agostini… - Cell Death …, 2020 - nature.com
The human zinc finger (C2H2-type) protein ZNF750 is a transcription factor regulated by p63
that plays a critical role in epithelial tissues homoeostasis, as well as being involved in the …