Gabriel C. Lander

Dr. Gabriel C. Lander

orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2009 in Journal of Structural Biology
Verified
Journal Article
Closed access
GLGabriel C. Lander
Gabriel C. Lander
SSScott M. Stagg
Scott M. Stagg
NVNeil R. Voss
Neil R. Voss
ACAnchi Cheng
Anchi Cheng
DFDenis Fellmann
Denis Fellmann
Bridget CarragherBridget Carragher
Bridget Carragher

1 January 2003 in Nucleic Acids Research
Verified
Journal Article
Closed access
SRSeung Yon Rhee
Seung Yon Rhee
WBWilliam Beavis
William Beavis
TBTanya Z Berardini
Tanya Z Berardini
GCGuanghong Chen
Guanghong Chen
DDDavid Dixon
David Dixon
PZPeifen Zhang
Peifen Zhang
Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.

1 May 2014 in Cell
Verified
Journal Article
Closed access
GAGregory M. Alushin
Gregory M. Alushin
GLGabriel C. Lander
Gabriel C. Lander
EKElizabeth H. Kellogg
Elizabeth H. Kellogg
RZRui Zhang
Rui Zhang
DBDavid Baker
David Baker
ENEva Nogales
Eva Nogales

22 June 2016 in Nature
Verified
Journal Article
Closed access
PDF file
MMMary E. Matyskiela
Mary E. Matyskiela
GLGang Lu
Gang Lu
TITakumi Ito
Takumi Ito
BPBarbra Pagarigan
Barbra Pagarigan
CLChin-Chun Lu
Chin-Chun Lu
PCPhilip P. Chamberlain
Philip P. Chamberlain

11 January 2012 in Nature
Verified
Journal Article
Open access
PDF file
GLGabriel C. Lander
Gabriel C. Lander
EEEric Estrin
Eric Estrin
MMMary E. Matyskiela
Mary E. Matyskiela
CBCharlene Bashore
Charlene Bashore
ENEva Nogales
Eva Nogales
AMAndreas Martin
Andreas Martin
The proteasome is the major ATP-dependent protease in eukaryotic cells, but limited structural information restricts a mechanistic understanding of its activities. The proteasome regulatory particle, consisting of the lid and base subcomplexes, recognizes and processes polyubiquitinated substrates. Here we used electron microscopy and a new heterologous expression system for the lid to delineate the complete subunit architecture of the regulatory particle from yeast. Our studies reveal the spatial arrangement of ubiquitin receptors, deubiquitinating enzymes and the protein unfolding machinery at subnanometre resolution, outlining the substrate’s path to degradation. Unexpectedly, the ATPase subunits within the base unfoldase are arranged in a spiral staircase, providing insight into potential mechanisms for substrate translocation through the central pore. Large conformational rearrangements of the lid upon holoenzyme formation suggest allosteric regulation of deubiquitination. We provide a structural basis for the ability of the proteasome to degrade a diverse set of substrates and thus regulate vital cellular processes.

1 June 2004 in Plant Physiology
Verified
Journal Article
Open access
PDF file
TBTanya Z. Berardini
Tanya Z. Berardini
SMSuparna Mundodi
Suparna Mundodi
LRLeonore Reiser
Leonore Reiser
EHEva Huala
Eva Huala
MGMargarita Garcia-Hernandez
Margarita Garcia-Hernandez
SRSeung Y. Rhee
Seung Y. Rhee
Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resource's goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species.