ReviewInternational journal of molecular sciences2016
Prediction of Protein-Protein Interactions by Evidence Combining Methods.
Review in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Homologous mapping yielded a comprehensive predicted protein-protein interaction network for peanut (Arachis hypogaea L.).BMC plant biology · 2024Article
- ProtInteract: A deep learning framework for predicting protein-protein interactions.Computational and structural biotechnology journal · 2023Article
- Large-Scale Protein Interactions Prediction by Multiple Evidence Analysis Associated With an In-Silico Curation Strategy.Frontiers in bioinformatics · 2021Article
- Comparison of the central human and mouse platelet signaling cascade by systems biological analysis.BMC genomics · 2020Article
- Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes.International journal of molecular sciences · 2020Article
- Prediction of Protein-Protein Interaction Sites Using Convolutional Neural Network and Improved Data Sets.International journal of molecular sciences · 2020Article
- ITRAQ-based proteomic analysis reveals possible target-related proteins in human adrenocortical adenomas.BMC genomics · 2019Article
- Development of an in silico method for the identification of subcomplexes involved in the biogenesis of multiprotein complexes in Saccharomyces cerevisiae.BMC systems biology · 2017Article
- Using Coexpression Protein Interaction Network Analysis to Identify Mechanisms of Danshensu Affecting Patients with Coronary Heart Disease.International journal of molecular sciences · 2017Article
- Across-proteome modeling of dimer structures for the bottom-up assembly of protein-protein interaction networks.BMC bioinformatics · 2017Article
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
Most cellular functions involve proteins' features based on their physical interactions with other partner proteins. Sketching a map of protein-protein interactions (PPIs) is therefore an important inception step towards understanding the basics of cell functions. Several experimental techniques operating in vivo or in vitro have made significant contributions to screening a large number of protein interaction partners, especially high-throughput experimental methods. However, computational approaches for PPI predication supported by rapid accumulation of data generated from experimental techniques, 3D structure definitions, and genome sequencing have boosted the map sketching of PPIs. In this review, we shed light on in silico PPI prediction methods that integrate evidence from multiple sources, including evolutionary relationship, function annotation, sequence/structure features, network topology and text mining. These methods are developed for integration of multi-dimensional evidence, for designing the strategies to predict novel interactions, and for making the results consistent with the increase of prediction coverage and accuracy.
Indexed as
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.