Protein‐protein interaction networks as miners of biological discovery

S Wang, R Wu, J Lu, Y Jiang, T Huang, YD Cai - Proteomics, 2022 - Wiley Online Library
Protein‐protein interactions (PPIs) form the basis of a myriad of biological pathways and
mechanism, such as the formation of protein complexes or the components of signaling …

Bioinformatics approaches for unveiling virus-host interactions

H Iuchi, J Kawasaki, K Kubo, T Fukunaga… - Computational and …, 2023 - Elsevier
Abstract The coronavirus disease-2019 (COVID-19) pandemic has elucidated major
limitations in the capacity of medical and research institutions to appropriately manage …

Alternating-direction-method of multipliers-based adaptive nonnegative latent factor analysis

Y Zhong, K Liu, S Gao, X Luo - IEEE Transactions on Emerging …, 2024 - ieeexplore.ieee.org
Large scale interaction data are frequently found in industrial applications related with Big
Data. Due to the fact that few interactions commonly happen among numerous nodes in real …

An alternating-direction-method of multipliers-incorporated approach to symmetric non-negative latent factor analysis

X Luo, Y Zhong, Z Wang, M Li - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
Large-scale undirected weighted networks are frequently encountered in big-data-related
applications concerning interactions among a large unique set of entities. Such a network …

Comparative interactomics for virus–human protein–protein interactions: DNA viruses versus RNA viruses

S Durmuş, KÖ Ülgen - FEBS open bio, 2017 - Wiley Online Library
Viruses are obligatory intracellular pathogens and completely depend on their hosts for
survival and reproduction. The strategies adopted by viruses to exploit host cell processes …

Predicting interactions between virus and host proteins using repeat patterns and composition of amino acids

S Alguwaizani, B Park, X Zhou… - Journal of healthcare …, 2018 - Wiley Online Library
Previous methods for predicting protein‐protein interactions (PPIs) were mainly focused on
PPIs within a single species, but PPIs across different species have recently emerged as an …

A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology

D Acharya, A Mukhopadhyay - Briefings in Functional Genomics, 2024 - academic.oup.com
Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse
biological interaction between different omics. Machine learning approaches have been …

Germline genomic patterns are associated with cancer risk, oncogenic pathways, and clinical outcomes

X Xu, Y Zhou, X Feng, X Li, M Asad, D Li, B Liao… - Science …, 2020 - science.org
There is an ongoing debate on the importance of genetic factors in cancer development,
where gene-centered cancer predisposition seems to show that only 5 to 10% of the cancer …

Deep variational graph autoencoders for novel host-directed therapy options against COVID-19

S Ray, S Lall, A Mukhopadhyay… - Artificial Intelligence in …, 2022 - Elsevier
The COVID-19 pandemic has been kee** asking urgent questions with respect to
therapeutic options. Existing drugs that can be repurposed promise rapid implementation in …

[HTML][HTML] Unveiling network-based functional features through integration of gene expression into protein networks

M Jalili, T Gebhardt, O Wolkenhauer… - … et Biophysica Acta (BBA …, 2018 - Elsevier
Decoding health and disease phenotypes is one of the fundamental objectives in
biomedicine. Whereas high-throughput omics approaches are available, it is evident that …