ArticleBioinformatics advances2025
Pharmacological assessment of
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
3 citing papers in PubMed.
- PhIP-driven prostate cancer involves key molecular regulators and immune microenvironment modulation.Frontiers in immunology · 2026Article
- Integrative transcriptomics and structure-based screening identifiesFrontiers in bioinformatics · 2026Article
- Exploring the impact of endocrine-disrupting chemicals on erectile dysfunction through network toxicology and machine learning.BMC pharmacology & toxicology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Cervical cancer remains a leading cause of gynecological mortality, with existing treatments often limited by resistance and suboptimal efficacy. While Results: From 158 bioactive compounds with favorable pharmacokinetic and drug-likeness properties, we predicted gene targets and intersected them with 1779 differentially expressed genes identified from bulk RNA-sequencing of 304 cervical cancer tumors and 47 normal cervical tissues. This yielded 43 Availability and implementation: The data supporting the findings of this study, including bulk RNA-seq gene expression data, survival, and phenotype data, are available through the TCGA database. These data can be accessed via the Xenabrowser platform (https://xenabrowser.net) using the reference identifier [TCGA Cervical Cancer (CESC)]. Corresponding healthy cervical tissue RNA-seq data, are available through the Genotype-Tissue Expression (GTEx) project (https://www.gtexportal.org/home/). The codes used for differential gene expression (DGE) analysis, pathway enrichment, and survival analysis, as well as scripts for generating volcano plots (DGE analysis), Kaplan-Meier survival plots, and boxplots (gene expression), and machine learning implementations are available on GitHub (https://github.com/Ponaskillzyy/Coffea_arabica_Potential_in_Cervical_Cancer).
Identifiers
What Socratic 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 Socratic graph.