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Carlos Bustamante

Researcher at Stanford University

Publications -  799
Citations -  122303

Carlos Bustamante is an academic researcher from Stanford University. The author has contributed to research in topics: Population & DNA. The author has an hindex of 161, co-authored 770 publications receiving 106053 citations. Previous affiliations of Carlos Bustamante include Lawrence Berkeley National Laboratory & University of California.

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Book ChapterDOI

Differential Polarization Imaging: Theory and Applications

TL;DR: In this article, a theory of differential polarization imaging using Mueller calculus is presented, which is applied to study the symmetry behavior of the Mueller matrix elements upon infinitesimal rotations of the optical components about the optical axis of the imaging system and obtain the phenomenological equations of the sixteen bright-field Mueller elements in terms of optical coefficients.
Book ChapterDOI

The Glean Machine

TL;DR: A sampling theory of selection and random genetic drift is developed for interpreting the numbers of wildtype and variant nucleotides found among the polymorphic sites present in sequences of multiple alleles of a gene, used to interpret the patterns of intrapopulation polymorphism of 28 genes in Escherichia coli and Salmonella enterica.
Proceedings ArticleDOI

Circular intensity differential scattering measurements in the soft x-ray region of the spectrum (~16 EV to 500 EV)

TL;DR: In this article, the authors proposed the use of recently developed technique of circular intensity differential scattering (CIDS), as extended to the soft x-ray region of the spectrum (16 eV to 500 eV), to study the higher order organization of the eukaryotic chromosome.
Posted Content

DeepTag: inferring all-cause diagnoses from clinical notes in under-resourced medical domain.

TL;DR: A deep learning algorithm, DeepTag, which automatically infers diagnostic codes from veterinary free text notes and enables automated disease annotation across a broad range of clinical diagnoses with minimal pre-processing.