Results 51 to 60 of about 245,963 (292)

Prediction and analysis of osteoarthritis hub genes with bioinformatics

Annals of Translational Medicine, 2023
Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery.
Zhong, Junqing, Xiang, Ding, Ma, Xinlong
openaire   +2 more sources

Co-expression network analysis identified six hub genes in association with progression and prognosis in human clear cell renal cell carcinoma (ccRCC)

Genomics Data, 2017
Human clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney tumors. We constructed a weighted gene co-expression network to identify gene modules associated with clinical features of ccRCC (n = 97).
Lushun Yuan, Liang Chen, Kaiyu Qian, Guofeng Qian, Chin-Lee Wu, Xinghuan Wang, Yu Xiao   +6 more
doaj   +1 more source

Identification of oxidative stress-related genes differentially expressed in Alzheimer’s disease and construction of a hub gene-based diagnostic model

Scientific Reports, 2023
Alzheimer’s disease (AD) is the most prevalent dementia disorder globally, and there are still no effective interventions for slowing or stopping the underlying pathogenic mechanisms.
Yanting Zhang, Hisanori Kiryu
doaj   +1 more source

Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin. [PDF]

, 2017
Human skin consists of multiple cell types, including epithelial, immune, and stromal cells. Transcriptomic analyses have previously been performed from bulk skin samples or from epithelial and immune cells expanded in cell culture.
Ahn, Richard S, Arron, Sarah T, Chang, David S, Gupta, Rashmi, Lai, Kevin, Lee, Kristina M, Liao, Wilson, Nititham, Joanne, Rosenblum, Michael, Taravati, Keyon   +9 more
core   +1 more source

Network Analyses of Differentially Expressed Genes in Osteoarthritis to Identify Hub Genes [PDF]

BioMed Research International, 2019
Background. Osteoarthritis (OA) is the most common degenerative disease in orthopedics. However, the cause and underlying molecular mechanisms are not clear. This study aims to identify the hub genes and pathways involved in the occurrence of osteoarthritis. Methods.
Zhaoyan Li, Lei Zhong, Zhenwu Du, Gaoyang Chen, Jing Shang, Qiwei Yang, Qingyu Wang, Yang Song, Guizhen Zhang   +8 more
openaire   +2 more sources

Identification and validation of hub genes for diabetic retinopathy

PeerJ, 2021
Background Diabetic retinopathy (DR) is characterized by a gradually progressive alteration in the retinal microvasculature that leads to middle-aged adult acquired persistent blindness. Limited research has been conducted on DR pathogenesis at the gene level.
Li Peng, Wei Ma, Qing Xie, Baihua Chen
openaire   +3 more sources

Screening of the key genes and signaling pathways for schizophrenia using bioinformatics and next generation sequencing data analysis

Italian Journal of Medicine
Schizophrenia is thought to be the most prevalent chronic psychiatric disorder. Researchers have identified numerous proteins associated with the occurrence and development of schizophrenia. This study aimed to identify potential core genes and pathways
Iranna Kotturshetti, Basavaraj Vastrad, Veena Kori, Chanabasayya Vastrad, Shivakumar Kotrashetti   +4 more
doaj   +1 more source

Identification of Hub Biomarkers and Immune-Related Pathways Participating in the Progression of Antineutrophil Cytoplasmic Antibody-Associated Glomerulonephritis

Frontiers in Immunology, 2022
BackgroundAntineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a systemic autoimmune disease that generally induces the progression of rapidly progressive glomerulonephritis (GN).
Meng-Di Xia, Meng-Di Xia, Rui-Ran Yu, Dong-Ming Chen, Dong-Ming Chen   +4 more
doaj   +1 more source

Maximal switchability of centralized networks

, 2016
We consider continuous time Hopfield-like recurrent networks as dynamical models for gene regulation and neural networks. We are interested in networks that contain n high-degree nodes preferably connected to a large number of Ns weakly connected ...
Morozov, Ivan, Radulescu, Ovidiu, Vakulenko, Sergei   +2 more
core   +3 more sources

Weighted-Lasso for Structured Network Inference from Time Course Data [PDF]

, 2009
We present a weighted-Lasso method to infer the parameters of a first-order vector auto-regressive model that describes time course expression data generated by directed gene-to-gene regulation networks. These networks are assumed to own a prior internal
Ambroise, Christophe, Charbonnier, Camille, Chiquet, Julien   +2 more
core   +2 more sources