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Eric Mjolsness

Researcher at University of California, Irvine

Publications -  175
Citations -  10398

Eric Mjolsness is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Artificial neural network & Regulation of gene expression. The author has an hindex of 40, co-authored 168 publications receiving 9630 citations. Previous affiliations of Eric Mjolsness include Washington University in St. Louis & University of California, San Diego.

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The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

TL;DR: This work summarizes the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks, a software-independent language for describing models common to research in many areas of computational biology.
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Fast and globally convergent pose estimation from video images

TL;DR: It is shown that the pose estimation problem can be formulated as that of minimizing an error metric based on collinearity in object (as opposed to image) space, and an iterative algorithm which directly computes orthogonal rotation matrices and which is globally convergent is derived.
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An auxin-driven polarized transport model for phyllotaxis

TL;DR: This work proposes a model that is based on the assumption that auxin influences the polarization of its own efflux within the meristem epidermis and shows how polarized transport can drive the formation of regular patterns.
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New algorithms for 2D and 3D point matching: pose estimation and correspondence

TL;DR: A fundamental open problem in computer vision—determining pose and correspondence between two sets of points in space—is solved with a novel, fast, robust and easily implementable algorithm using a combination of optimization techniques.
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A connectionist model of development

TL;DR: A phenomenological modeling framework for development based on a connectionist or "neural net" dynamics for biochemical regulators coupled to "grammatical rules" which describe certain features of the birth, growth, and death of cells, synapses and other biological entities is presented.