ArticlePloS one2017
PICKLE 2.0: A human protein-protein interaction meta-database employing data integration via genetic information ontology.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Protein-protein interaction network-based integration of GWAS and functional data for blood pressure regulation analysis.Human genomics · 2024Article
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- Significance of Catecholamine Biosynthetic/Metabolic Pathway in SARS-CoV-2 Infection and COVID-19 Severity.Cells · 2022Article
- A rare human centenarian variant of SIRT6 enhances genome stability and interaction with Lamin A.The EMBO journal · 2022Article
- Tissue-wide cell-specific proteogenomic modeling reveals novel candidate risk genes in autism spectrum disorders.NPJ systems biology and applications · 2022Article
- How Far Are We from the Completion of the Human Protein Interactome Reconstruction?Biomolecules · 2022Article
- Systems-Level Mapping of Cancer Testis Antigen 1b/a to Sarcoma Pathways Identifies Activated Ran Binding-2 E3 SUMO-Protein Ligase and Transducin-Like Enhancer Protein 1.Frontiers in genetics · 2022Article
- Using expression quantitative trait loci data and graph-embedded neural networks to uncover genotype-phenotype interactions.Frontiers in genetics · 2022Article
- Identification of differentially expressed genes and pathways crosstalk analysis in Rheumatoid and Osteoarthritis using next-generation sequencing and protein-protein networks.Saudi journal of biological sciences · 2021Article
- IHP-PING-generating integrated human protein-protein interaction networks on-the-fly.Briefings in bioinformatics · 2021Article
- Linking genotype to phenotype in multi-omics data of small sample.BMC genomics · 2021Article
- HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis.Database : the journal of biological databases and curation · 2021Article
- Deciphering cell-cell interactions and communication from gene expression.Nature reviews. Genetics · 2021Review
- Elucidating the network features and evolutionary attributes of intra- and interspecific protein-protein interactions between human and pathogenic bacteria.Scientific reports · 2021Article
- Identifying Key Genes for Nasopharyngeal Carcinoma by Prioritized Consensus Differentially Expressed Genes Caused by Aberrant Methylation.Journal of Cancer · 2021Article
- Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes.Patterns (New York, N.Y.) · 2020Article
- A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data.BMC bioinformatics · 2020Article
- Mutation severity spectrum of rare alleles in the human genome is predictive of disease type.PLoS computational biology · 2020Article
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3 authors.
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Abstract
It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes.
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