Identification of potential key genes related to idiopathic male infertility using RNA-sequencing data: an approach.

Among reproductive health problems, idiopathic infertility affects married couples. The current diagnosis of male infertility focuses on the concentration, motility, and morphology of sperm in the ejaculate. Since the molecular mechanism of idiopathic infertility is unknown, identification of Differentially Expressed Genes (DEGs) among the control and idiopathic infertile male can shed light on diagnosis and treatment.

Identification of novel lncRNA by reanalysis of RNA-seq data in Zika Virus Infected hiNPCs.

Unlabelled: The Zika Virus (ZIKV) infection is a serious, public health concern with no vaccines or antiviral treatments. This study aims to identify the differentially expressed long non-coding RNAs (lncRNAs) in ZIKV infected human-induced neuroprogenitor cells (hiNPCs). Though lncRNA is well-known for its role in gene regulation, its role in ZIKV infection remains unclear.

Ebolabase: Zaire ebolavirus-human protein interaction database for drug-repurposing.

Ebola Virus (EBOV) is one of the deadliest pathogenic virus which causes hemorrhagic fever. Though many Ebola-human interaction studies and databases are already reported, the unavailability of an adequate model and lack of publically accessible resources requires a comprehensive study to curate the Ebola-Human-Drug interactions. In total, 270 human proteins interacted with EBOV are collected from published experimental evidence.

Understanding of Zaire ebolavirus-human protein interaction for drug repurposing.

The Ebola virus is a human aggressive pathogen causes Ebola virus disease that threatens public health, for which there is no Food Drug Administration approved medication. Drug repurposing is an alternative method to find the novel indications of known drugs to treat the disease effectively at low cost. The present work focused on understanding the host-virus interaction as well as host virus drug interaction to identify the disease pathways and host-directed drug targets.

Comprehensive analysis of dysregulated lncRNAs and their competing endogenous RNA network in triple-negative breast cancer.

The study aimed to explore the molecular mechanism underlying triple-negative breast cancer (TNBC) and to identify their potential diagnostic/prognostic biomarkers. The differentially expressed lncRNAs (DElncRNAs) were identified by meta-analysis and machine learning feature selection methods. The dysregulated lncRNA-miRNA-mRNA network was constructed based on the competing endogenous RNA (ceRNA) hypothesis.

Identification of dysregulated miRNAs in triple negative breast cancer: A meta-analysis approach.

Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with poor clinical outcomes and lack of approved targeted therapy. Dysregulated microRNAs (miRNAs) have been considered a promising biomarker, which plays an important role in the tumorigenesis of human cancer. Due to the increase in miRNA profiling datasets of TNBC, a proper analysis is required for studying.

Integrated network analysis and machine learning approach for the identification of key genes of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) has attracted more attention compared with other breast cancer subtypes due to its aggressive nature, poor prognosis, and chemotherapy remains the mainstay of treatment with no other approved targeted therapy. Therefore, the study aimed to discover more promising therapeutic targets and investigating new insights of biological mechanism of TNBC. Six microarray data sets consisting of 463 non-TNBC and 405 TNBC samples were mined from Gene Expression Omnibus.

Identification of Hub Genes and Pathways in Zika Virus Infection Using RNA-Seq Data: A Network-Based Computational Approach.

Zika virus (ZIKV), a single-strand RNA flavivirus, is transmitted primarily through Aedes aegypti. The recent outbreaks in America and unexpected association between ZIKV infection and birth defects have triggered the global attention. This vouches to understand the molecular mechanisms of ZIKV infection to develop effective drug therapy.

ZikaBase: An integrated ZIKV- Human Interactome Map database.

Re-emergence of ZIKV has caused infections in more than 1.5 million people. The molecular mechanism and pathogenesis of ZIKV is not well explored due to unavailability of adequate model and lack of publically accessible resources to provide information of ZIKV-Human protein interactome map till today.