Adaptive boosting-based computational model for predicting potential miRNA-disease associations

Y Zhao, X Chen, J Yin - Bioinformatics, 2019 - academic.oup.com
Motivation Recent studies have shown that microRNAs (miRNAs) play a critical part in
several biological processes and dysregulation of miRNAs is related with numerous …

[HTML][HTML] HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction

X Chen, CC Yan, X Zhang, ZH You, YA Huang… - Oncotarget, 2016 - ncbi.nlm.nih.gov
Recently, microRNAs (miRNAs) have drawn more and more attentions because
accumulating experimental studies have indicated miRNA could play critical roles in multiple …

miRNA‐disease association prediction with collaborative matrix factorization

Z Shen, YH Zhang, K Han, AK Nandi, B Honig… - …, 2017 - Wiley Online Library
As one of the factors in the noncoding RNA family, microRNAs (miRNAs) are involved in the
development and progression of various complex diseases. Experimental identification of …

The role of network science in glioblastoma

MB Lopes, EP Martins, S Vinga, BM Costa - Cancers, 2021 - mdpi.com
Simple Summary Knowledge extraction from cancer genomic studies is continuously
challenged by the fast-growing technological advances generating high-dimensional data …

Pathway map** and development of disease‐specific biomarkers: protein‐based network biomarkers

H Chen, Z Zhu, Y Zhu, J Wang, Y Mei… - Journal of cellular and …, 2015 - Wiley Online Library
It is known that a disease is rarely a consequence of an abnormality of a single gene, but
reflects the interactions of various processes in a complex network. Annotated molecular …

Disease gene prediction for molecularly uncharacterized diseases

JJ Cáceres, A Paccanaro - PLoS computational biology, 2019 - journals.plos.org
Network medicine approaches have been largely successful at increasing our knowledge of
molecularly characterized diseases. Given a set of disease genes associated with a …

Cooperative co-evolutionary module identification with application to cancer disease module discovery

S He, G Jia, Z Zhu, DA Tennant… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Module identification or community detection in complex networks has become increasingly
important in many scientific fields because it provides insight into the relationship and …

Identification of key modules and hub genes in glioblastoma multiforme based on co‐expression network analysis

C Li, B Pu, L Gu, M Zhang, H Shen, Y Yuan… - FEBS Open …, 2021 - Wiley Online Library
Glioblastoma multiforme (GBM) is the most malignant primary tumour in the central nervous
system, but the molecular mechanisms underlying its pathogenesis remain unclear. In this …

Scouting for common genes in the heterogenous hypoxic tumor microenvironment and their validation in glioblastoma

A Bhushan, R Kumari, T Srivastava - 3 Biotech, 2021 - Springer
Investigating the therapeutic and prognostic potential of genes in the heterogeneous
hypoxic niche of glioblastoma. We have analyzed RNA expression of U87MG cells cultured …

[HTML][HTML] Modular transcriptional repertoire and MicroRNA target analyses characterize genomic dysregulation in the thymus of Down syndrome infants

CA Moreira-Filho, SY Bando, FB Bertonha, FN Silva… - Oncotarget, 2016 - ncbi.nlm.nih.gov
Trisomy 21-driven transcriptional alterations in human thymus were characterized through
gene coexpression network (GCN) and miRNA-target analyses. We used whole thymic …