ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
CodLncScape Provides a Self-Enriching Framework for the Systematic Collection and Exploration of Coding LncRNAs.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 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.
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Who cites it
40 citing papers in PubMed.
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- Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective.Briefings in bioinformatics · 2026Review
- HybridGNN: a graph neural network approach for human miRNA-disease association prediction.Bioinformatics (Oxford, England) · 2026Article
- cncFinder: A graph-attention-network-based interpretable learning model to identify bifunctional long non-coding RNAs.Molecular therapy. Nucleic acids · 2026Article
- AMP-CapsNet: a multi-view feature fusion approach for antimicrobial peptide prediction using capsule networks.Genomics & informatics · 2026Article
- CMsiRNAdb: a database of chemically modified SiRNA silencing efficiency for nucleic acid drug design.BMC bioinformatics · 2026Article
- Copper-Iron Cell Death Axis: Mechanistic Crosstalk, Disease Implications and an Integrated Metallo-Redox-Metabolic Framework.International journal of biological sciences · 2026Review
- RWRGDR: Random Walk and GraphSAGE-based Framework for Enhanced Drug Repositioning.Current drug targets · 2026Article
- An Explainable Deep Learning Model for Clathrin Protein Prediction Using a DCT-Enhanced Position-Specific Scoring Matrix.Current drug targets · 2026Article
- Interferon-primed immune landscapes predict immune-related adverse events during immune checkpoint inhibitor therapy.Frontiers in cell and developmental biology · 2026Article
- Omics landscapes in molecular mechanisms withFood chemistry. Molecular sciences · 2025Review
- PCBert-Kla: an efficient prediction method for lysine lactylation sites based on ProtBert and fusion of physicochemical features.Briefings in bioinformatics · 2025Article
- Exploring claudin proteins: from sequence motifs to their impact on tight junction-mediated signaling pathways.Amino acids · 2025Review
- Multi-omics integrative analysis reveals novel genetic loci and candidate genes for ischemic stroke.Molecular therapy. Nucleic acids · 2025Article
- Computational toxicology in drug discovery: applications of artificial intelligence in ADMET and toxicity prediction.Briefings in bioinformatics · 2025Review
- Navigating the 3D genome at single-cell resolution: techniques, computation, and mechanistic landscapes.Briefings in bioinformatics · 2025Review
- NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides.BMC biology · 2025Article
- An artificial intelligence-based approach for identifying the proteins regulating liquid-liquid phase separation.Briefings in bioinformatics · 2025Article
- TransMA: an explainable multi-modal deep learning model for predicting properties of ionizable lipid nanoparticles in mRNA delivery.Briefings in bioinformatics · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Recent studies have revealed that numerous lncRNAs can translate proteins under specific conditions, performing diverse biological functions, thus termed coding lncRNAs. Their comprehensive landscape, however, remains elusive due to this field's preliminary and dispersed nature. This study introduces codLncScape, a framework for coding lncRNA exploration consisting of codLncDB, codLncFlow, codLncWeb, and codLncNLP. Specifically, it contains a manually compiled knowledge base, codLncDB, encompassing 353 coding lncRNA entries validated by experiments. Building upon codLncDB, codLncFlow investigates the expression characteristics of these lncRNAs and their diagnostic potential in the pan-cancer context, alongside their association with spermatogenesis. Furthermore, codLncWeb emerges as a platform for storing, browsing, and accessing knowledge concerning coding lncRNAs within various programming environments. Finally, codLncNLP serves as a knowledge-mining tool to enhance the timely content inclusion and updates within codLncDB. In summary, this study offers a well-functioning, content-rich ecosystem for coding lncRNA research, aiming to accelerate systematic studies in this field.
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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.