ArticleBioMed research international2013
Prediction of gene phenotypes based on GO and KEGG pathway enrichment scores.
Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed.
- Incorporating GO/KEGG Functional Annotations Improves the Accuracy and Stability of Genomic Prediction Across Diverse Beef Cattle Populations.Animals : an open access journal from MDPI · 2026Article
- Molecular Subtypes and Risk Prediction Model Based on Malignant Cell Differentiation Trajectories in Breast Cancer.Journal of cellular and molecular medicine · 2025Article
- Ferroptosis-related genes participate in the microglia-induced neuroinflammation of spinal cord injury via NF-κB signaling: evidence from integrated single-cell and spatial transcriptomic analysis.Journal of translational medicine · 2025Article
- Article
- Prevention of neointimal hyperplasia after coronary artery bypass graft via local delivery of sirolimus and rosuvastatin: network pharmacology and in vivo validation.Journal of translational medicine · 2024Article
- Article
- Comparative Transcriptome Analysis of Deep-Rooting and Shallow-Rooting Potato (Plants (Basel, Switzerland) · 2022Article
- Fine-mapping and association analysis of candidate genes for papilla number in sea cucumber,Marine life science & technology · 2022Article
- Spatial Transcriptomic Analysis Using R-Based Computational Machine Learning Reveals the Genetic Profile of Yang or Yin Deficiency Syndrome in Chinese Medicine Theory.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Study on mechanism of matrine in treatment of COVID-19 combined with liver injury by network pharmacology and molecular docking technology.Drug delivery · 2021Article
- Article
- The establishment of a hub differential gene model to predict prognosis in stage II and III right- and left-sided colon cancer patients.Annals of translational medicine · 2021Article
- Genome-Wide Association Study RevealsFrontiers in genetics · 2021Article
- Identification of Key eRNAs for Spinal Cord Injury by Integrated Multinomial Bioinformatics Analysis.Frontiers in cell and developmental biology · 2021Article
- A ceRNA network and a potential regulatory axis in gastric cancer with different degrees of immune cell infiltration.Cancer science · 2020Article
- iTRAQ-based proteomics analysis on insomnia rats treated with Mongolian medical warm acupuncture.Bioscience reports · 2020Article
- The prognostic value of COL3A1/FBN1/COL5A2/SPARC-mir-29a-3p-H19 associated ceRNA network in Gastric Cancer through bioinformatic exploration.Journal of Cancer · 2020Article
- Role of theMolecular vision · 2020Article
- Comprehensive Analysis of Aberrantly Expressed ceRNA network in gastric cancer with and withoutJournal of Cancer · 2019Article
- Integrated analysis of dysregulated long non-coding RNAs/microRNAs/mRNAs in metastasis of lung adenocarcinoma.Journal of translational medicine · 2018Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Observing what phenotype the overexpression or knockdown of gene can cause is the basic method of investigating gene functions. Many advanced biotechnologies, such as RNAi, were developed to study the gene phenotype. But there are still many limitations. Besides the time and cost, the knockdown of some gene may be lethal which makes the observation of other phenotypes impossible. Due to ethical and technological reasons, the knockdown of genes in complex species, such as mammal, is extremely difficult. Thus, we proposed a new sequence-based computational method called kNNA-based method for gene phenotypes prediction. Different to the traditional sequence-based computational method, our method regards the multiphenotype as a whole network which can rank the possible phenotypes associated with the query protein and shows a more comprehensive view of the protein's biological effects. According to the prediction result of yeast, we also find some more related features, including GO and KEGG information, which are making more contributions in identifying protein phenotypes. This method can be applied in gene phenotype prediction in other species.
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.