ArticleBioinformatics and biology insights2022
Multiple Myeloma: Bioinformatic Analysis for Identification of Key Genes and Pathways.
Article in Bioinformatics and biology insights, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
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- Efficacy and potential toxicity of Duhuo Qinjiao Decoction in osteoarthritis via the NF-κB pathway.Clinical rheumatology · 2026Article
- Integrative Network Analysis of Single-Cell RNA Findings and a Priori Knowledge Highlights Gene Regulators in Multiple Myeloma Progression.International journal of molecular sciences · 2026Article
- Comprehensive Bioinformatic Analysis Reveals Survival-Associated Hub Genes and MicroRNAs in Multiple Myeloma Patients.Iranian journal of biotechnology · 2025Article
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- Integrative Analysis of the Impact of Prenatal Depression on the Newborn Intestinal Microbiota.Central nervous system agents in medicinal chemistry · 2025Article
- The mechanism of LSM2 in the progression of live hepatocellular carcinoma was analyzed based on bioinformatics.Medical oncology (Northwood, London, England) · 2023Article
- The TT Genotype of theCells · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple myeloma (MM) is a hematological malignancy in which monoclonal plasma cells multiply in the bone marrow and monoclonal immunoglobulins are overproduced in older people. Several molecular and cytogenetic advances allow scientists to identify several genetic and chromosomal abnormalities that cause the disease. The comprehension of the pathophysiology of MM requires an understanding of the characteristics of malignant clones and the changes in the bone marrow microenvironment. This study aims to identify the central genes and to determine the key signaling pathways in MM by in silico approaches. A list of 114 differentially expressed genes (DEGs) is important in the prognosis of MM. The DEGs are collected from scientific publications and databases (https://www.ncbi.nlm.nih.gov/). These data are analyzed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software (https://string-db.org/) through the construction of protein-protein interaction (PPI) networks and enrichment analysis of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, by CytoHubba, AutoAnnotate, Bingo Apps plugins in Cytoscape software (https://cytoscape.org/) and by DAVID database (https://david.ncifcrf.gov/). The analysis of the results shows that there are 7 core genes, including
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.