ArticleBioinformatics (Oxford, England)2023
CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts.Nature communications · 2024Article
- longmixr: a tool for robust clustering of high-dimensional cross-sectional and longitudinal variables of mixed data types.Bioinformatics (Oxford, England) · 2024Article
- Neutrophil activation and clonal CAR-T re-expansion underpinning cytokine release syndrome during ciltacabtagene autoleucel therapy in multiple myeloma.Nature communications · 2024Article
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Authors and funding
14 authors.
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Abstract
motivationThe transition from evaluating a single time point to examining the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and clustering challenging.
resultsWe developed CONNECTOR, a data-driven framework able to analyze and inspect longitudinal data in a straightforward and revealing way. When used to analyze tumor growth kinetics over time in 1599 patient-derived xenograft growth curves from ovarian and colorectal cancers, CONNECTOR allowed the aggregation of time-series data through an unsupervised approach in informative clusters. We give a new perspective of mechanism interpretation, specifically, we define novel model aggregations and we identify unanticipated molecular associations with response to clinically approved therapies. AVAILABILITY AND IMPLEMENTATION: CONNECTOR is freely available under GNU GPL license at https://qbioturin.github.io/connector and https://doi.org/10.17504/protocols.io.8epv56e74g1b/v1.
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