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Jared C. Roach

Researcher at Institute for Systems Biology

Publications -  74
Citations -  8741

Jared C. Roach is an academic researcher from Institute for Systems Biology. The author has contributed to research in topics: Gene & Population. The author has an hindex of 37, co-authored 68 publications receiving 8033 citations. Previous affiliations of Jared C. Roach include University of Washington & Seattle Children's Research Institute.

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Parking Strategies for Genome Sequencing

TL;DR: A mathematical model with a generalization to allow for overlaps is presented that predicts multiple parameters, including progress, costs, and the distribution of gap sizes left by a parking strategy, and is generalizable to many other strategies.
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Predictive Analytics In Healthcare: Medications as a Predictor of Medical Complexity.

Abstract: Children with special healthcare needs (CSHCN) require health and related services that exceed those required by most hospitalized children. A small but growing and important subset of the CSHCN group includes medically complex children (MCCs). MCCs typically have comorbidities and disproportionately consume healthcare resources. To enable strategic planning for the needs of MCCs, simple screens to identify potential MCCs rapidly in a hospital setting are needed. We assessed whether the number of medications used and the class of those medications correlated with MCC status. Retrospective analysis of medication data from the inpatients at Seattle Children's Hospital found that the numbers of inpatient and outpatient medications significantly correlated with MCC status. Numerous variables based on counts of medications, use of individual medications, and use of combinations of medications were considered, resulting in a simple model based on three different counts of medications: outpatient and in...
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Optimization of restriction fragment DNA mapping.

TL;DR: It is observed that the cost of an optimal mapping strategy is approximately proportional to the target size, and considerable effort is nonetheless required: for large-scale sequencing projects with up-front mapping, mapping will be a non-negligible fraction of the total sequencing cost.
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Expectation and variance of true and false fragment matches in DNA restriction mapping.

TL;DR: A geometrical probability approach is used to develop exact integral formulas and first-order approximations for the expected number and variance of classes of fragment pairs that will be identified falsely as matching in a DNA mapping project.