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David J. Lockhart

Researcher at Affymetrix

Publications -  95
Citations -  31553

David J. Lockhart is an academic researcher from Affymetrix. The author has contributed to research in topics: Nucleic acid & Oligonucleotide. The author has an hindex of 49, co-authored 95 publications receiving 30797 citations. Previous affiliations of David J. Lockhart include Ambit Biosciences & Thermo Fisher Scientific.

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Expression monitoring by hybridization to high density oligonucleotide arrays

TL;DR: In this article, the authors proposed a method for monitoring the expression levels of a multiplicity of genes by hybridizing a nucleic acid sample to a high density array of oligonucleotide probes and quantifying the hybridized nucleic acids in the array.
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Functional Characterization of the S. cerevisiae Genome by Gene Deletion and Parallel Analysis

TL;DR: A total of 6925 Saccharomyces cerevisiae strains were constructed, by a high-throughput strategy, each with a precise deletion of one of 2026 ORFs (more than one-third of the ORFs in the genome), finding that 17 percent were essential for viability in rich medium.
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High density synthetic oligonucleotide arrays

TL;DR: An approach in which sequence information is used directly to design high–density, two–dimensional arrays of synthetic oligonucleotides is developed, which have been designed and used for quantitative and highly parallel measurements of gene expression, to discover polymorphic loci and to detect the presence of thousands of alternative alleles.
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A Genome-Wide Transcriptional Analysis of the Mitotic Cell Cycle

TL;DR: The genome-wide characterization of mRNA transcript levels during the cell cycle of the budding yeast S. cerevisiae indicates a mechanism for local chromosomal organization in global mRNA regulation and links a range of human genes to cell cycle period-specific biological functions.
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Genomics, gene expression and DNA arrays.

TL;DR: Measurements of gene expression and other applications of arrays embody much of what is implied by the term ‘genomics’; they are broad in scope, large in scale, and take advantage of all available sequence information for experimental design and data interpretation in pursuit of biological understanding.