Methods of integrating data to uncover genotype–phenotype interactions
By Marylyn DeRiggi Ritchie, Emily Rose Holzinger, Ruowang Li, Sarah A. Pendergrass, Dokyoon Kim. Nature reviews genetics, 2015
983 citations recorded by the source corpus.
Subfields: Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/62b8c1e33b3e81b4a248999f68e19c07a2da025f
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Citations in the corpus
- Multi-Value Rule Sets (2017, background): “Recent works focus more on combining multiple values into a single feature [16,18].”
- Rewiring of the Fruit Metabolome in Tomato Breeding. (2018, methodology): “Owing to the limitations of single-data-type approaches, combining multiple datasets can Cell 172, 249–261, January 11, 2018 257 compensate for missing or unreliable information in any single data type (Ritchie et al., 2015).”
- More Is Better: Recent Progress in Multi-Omics Data Integration Methods (2017, methodology): “Multi-step (or multi-stage) methods are commonly used to find relationships between the different data types first, and then between the data types and the trait or phenotypes (Ritchie et al., 2015).”
- Transfer Learning for Molecular Cancer Classification Using Deep Neural Networks (2019, background): “be enough for complete information or good characterization; hence predictive models are often designed to exploit multiple heterogeneous data sources [48].”
- What is Speciation Genomics? The roles of ecology, gene flow, and genomic architecture in the formation of species (2018, background): “, 2011) and can be an alternative or complement to genome scans for identifying barrier loci (Wang, Gerstein & Snyder, 2009; Jeukens et al., 2010; Poelstra et al., 2014; Ritchie et al., 2015; Rafati et al., 2018), which may also themselves represent regulatory divergence (Mack & Nachman, 2017).”
- Metaheuristic design of feedforward neural networks: A review of two decades of research (2017, background): “On the other hand, integration of data or of the models for that matter for the heterogeneous data generated or gathered from different instruments and data-generation processes is a significant research problem [344,345].”
- Enabling semantic queries across federated bioinformatics databases (2019, neutral): “BMC Bioinformatics, 18(1):93, February 2017.”
- Integrative omics for health and disease (2018, neutral): “73 ).”
- MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis (2018, background): “However, integrating multiple omics data and interpreting these results at a systems level has become a significant challenge (40,41).”
- Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources (2020, background): “One can analyze or model each omic modality separately and then integrate results (a posteriori integration) or one can integrate data for all omic modalities before any statistical or computational modeling (a priori integration) [14].”