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Dive into the research topics where Benjamin A. Shoemaker is active.

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Featured researches published by Benjamin A. Shoemaker.


Nucleic Acids Research | 2004

CDD: a Conserved Domain Database for protein classification

John B. Anderson; Praveen F. Cherukuri; Carol DeWeese-Scott; Lewis Y. Geer; Marc Gwadz; Siqian He; David I. Hurwitz; John D. Jackson; Zhaoxi Ke; Christopher J. Lanczycki; Cynthia A. Liebert; Chunlei Liu; Fu Lu; Gabriele H. Marchler; Mikhail Mullokandov; Benjamin A. Shoemaker; Vahan Simonyan; James S. Song; Paul A. Thiessen; Roxanne A. Yamashita; Jodie J. Yin; Dachuan Zhang; Stephen H. Bryant

The Conserved Domain Database (CDD) is the protein classification component of NCBIs Entrez query and retrieval system. CDD is linked to other Entrez databases such as Proteins, Taxonomy and PubMed®, and can be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=cdd. CD-Search, which is available at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, is a fast, interactive tool to identify conserved domains in new protein sequences. CD-Search results for protein sequences in Entrez are pre-computed to provide links between proteins and domain models, and computational annotation visible upon request. Protein–protein queries submitted to NCBIs BLAST search service at http://www.ncbi.nlm.nih.gov/BLAST are scanned for the presence of conserved domains by default. While CDD started out as essentially a mirror of publicly available domain alignment collections, such as SMART, Pfam and COG, we have continued an effort to update, and in some cases replace these models with domain hierarchies curated at the NCBI. Here, we report on the progress of the curation effort and associated improvements in the functionality of the CDD information retrieval system.


Nucleic Acids Research | 2016

PubChem Substance and Compound databases

Sunghwan Kim; Paul A. Thiessen; Evan Bolton; Jie Chen; Gang Fu; Asta Gindulyte; Lianyi Han; Jane He; Siqian He; Benjamin A. Shoemaker; Jiyao Wang; Bo Yu; Jian-Jian Zhang; Stephen H. Bryant

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public repository for information on chemical substances and their biological activities, launched in 2004 as a component of the Molecular Libraries Roadmap Initiatives of the US National Institutes of Health (NIH). For the past 11 years, PubChem has grown to a sizable system, serving as a chemical information resource for the scientific research community. PubChem consists of three inter-linked databases, Substance, Compound and BioAssay. The Substance database contains chemical information deposited by individual data contributors to PubChem, and the Compound database stores unique chemical structures extracted from the Substance database. Biological activity data of chemical substances tested in assay experiments are contained in the BioAssay database. This paper provides an overview of the PubChem Substance and Compound databases, including data sources and contents, data organization, data submission using PubChem Upload, chemical structure standardization, web-based interfaces for textual and non-textual searches, and programmatic access. It also gives a brief description of PubChem3D, a resource derived from theoretical three-dimensional structures of compounds in PubChem, as well as PubChemRDF, Resource Description Framework (RDF)-formatted PubChem data for data sharing, analysis and integration with information contained in other databases.


Nucleic Acids Research | 2012

PubChem's BioAssay Database

Yanli Wang; Jewen Xiao; Tugba O. Suzek; Jian Zhang; Jiyao Wang; Zhigang Zhou; Lianyi Han; Karen Karapetyan; Svetlana Dracheva; Benjamin A. Shoemaker; Evan Bolton; Asta Gindulyte; Stephen H. Bryant

PubChem (http://pubchem.ncbi.nlm.nih.gov) is a public repository for biological activity data of small molecules and RNAi reagents. The mission of PubChem is to deliver free and easy access to all deposited data, and to provide intuitive data analysis tools. The PubChem BioAssay database currently contains 500 000 descriptions of assay protocols, covering 5000 protein targets, 30 000 gene targets and providing over 130 million bioactivity outcomes. PubChems bioassay data are integrated into the NCBI Entrez information retrieval system, thus making PubChem data searchable and accessible by Entrez queries. Also, as a repository, PubChem constantly optimizes and develops its deposition system answering many demands of both high- and low-volume depositors. The PubChem information platform allows users to search, review and download bioassay description and data. The PubChem platform also enables researchers to collect, compare and analyze biological test results through web-based and programmatic tools. In this work, we provide an update for the PubChem BioAssay resource, including information content growth, data model extension and new developments of data submission, retrieval, analysis and download tools.


PLOS Computational Biology | 2007

Deciphering protein-protein interactions. Part I. Experimental techniques and databases.

Benjamin A. Shoemaker; Anna R. Panchenko

Proteins interact with each other in a highly specific manner, and protein interactions play a key role in many cellular processes; in particular, the distortion of protein interfaces may lead to the development of many diseases. To understand the mechanisms of protein recognition at the molecular level and to unravel the global picture of protein interactions in the cell, different experimental techniques have been developed. Some methods characterize individual protein interactions while others are advanced for screening interactions on a genome-wide scale. In this review we describe different experimental techniques of protein interaction identification together with various databases which attempt to classify the large array of experimental data. We discuss the main promises and pitfalls of different methods and present several approaches to verify and validate the diverse experimental data produced by high-throughput techniques.


PLOS Computational Biology | 2007

Deciphering protein-protein interactions. Part II. Computational methods to predict protein and domain interaction partners.

Benjamin A. Shoemaker; Anna R. Panchenko

Recent advances in high-throughput experimental methods for the identification of protein interactions have resulted in a large amount of diverse data that are somewhat incomplete and contradictory. As valuable as they are, such experimental approaches studying protein interactomes have certain limitations that can be complemented by the computational methods for predicting protein interactions. In this review we describe different approaches to predict protein interaction partners as well as highlight recent achievements in the prediction of specific domains mediating protein-protein interactions. We discuss the applicability of computational methods to different types of prediction problems and point out limitations common to all of them.


Nucleic Acids Research | 2010

An overview of the PubChem BioAssay resource

Yanli Wang; Evan Bolton; Svetlana Dracheva; Karen Karapetyan; Benjamin A. Shoemaker; Tugba O. Suzek; Jiyao Wang; Jewen Xiao; Jian Zhang; Stephen H. Bryant

The PubChem BioAssay database (http://pubchem.ncbi.nlm.nih.gov) is a public repository for biological activities of small molecules and small interfering RNAs (siRNAs) hosted by the US National Institutes of Health (NIH). It archives experimental descriptions of assays and biological test results and makes the information freely accessible to the public. A PubChem BioAssay data entry includes an assay description, a summary and detailed test results. Each assay record is linked to the molecular target, whenever possible, and is cross-referenced to other National Center for Biotechnology Information (NCBI) database records. ‘Related BioAssays’ are identified by examining the assay target relationship and activity profile of commonly tested compounds. A key goal of PubChem BioAssay is to make the biological activity information easily accessible through the NCBI information retrieval system-Entrez, and various web-based PubChem services. An integrated suite of data analysis tools are available to optimize the utility of the chemical structure and biological activity information within PubChem, enabling researchers to aggregate, compare and analyze biological test results contributed by multiple organizations. In this work, we describe the PubChem BioAssay database, including data model, bioassay deposition and utilities that PubChem provides for searching, downloading and analyzing the biological activity information contained therein.


Nucleic Acids Research | 1999

MMDB: Entrez's 3D-structure database

Yanli Wang; John B. Anderson; Jie Chen; Lewis Y. Geer; Siqian He; David I. Hurwitz; Cynthia A. Liebert; Thomas Madej; Gabriele H. Marchler; Anna R. Panchenko; Benjamin A. Shoemaker; James S. Song; Paul A. Thiessen; Roxanne A. Yamashita; Stephen H. Bryant

Three-dimensional structures are now known within many protein families and it is quite likely, in searching a sequence database, that one will encounter a homolog with known structure. The goal of Entrezs 3D-structure database is to make this information, and the functional annotation it can provide, easily accessible to molecular biologists. To this end Entrezs search engine provides three powerful features. (i) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (ii) Links between databases; one may search by term matching in MEDLINE, for example, and link to 3D structures reported in these articles. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view molecular-graphic and alignment displays, to infer approximate 3D structure. In this article we focus on two features of Entrezs Molecular Modeling Database (MMDB) not described previously: links from individual biopolymer chains within 3D structures to a systematic taxonomy of organisms represented in molecular databases, and links from individual chains (and compact 3D domains within them) to structure neighbors, other chains (and 3D domains) with similar 3D structure. MMDB may be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Structure.


Nucleic Acids Research | 2014

PubChem BioAssay: 2014 update

Yanli Wang; Tugba O. Suzek; Jian Zhang; Jiyao Wang; Siqian He; Tiejun Cheng; Benjamin A. Shoemaker; Asta Gindulyte; Stephen H. Bryant

PubChem’s BioAssay database (http://pubchem.ncbi.nlm.nih.gov) is a public repository for archiving biological tests of small molecules generated through high-throughput screening experiments, medicinal chemistry studies, chemical biology research and drug discovery programs. In addition, the BioAssay database contains data from high-throughput RNA interference screening aimed at identifying critical genes responsible for a biological process or disease condition. The mission of PubChem is to serve the community by providing free and easy access to all deposited data. To this end, PubChem BioAssay is integrated into the National Center for Biotechnology Information retrieval system, making them searchable by Entrez queries and cross-linked to other biomedical information archived at National Center for Biotechnology Information. Moreover, PubChem BioAssay provides web-based and programmatic tools allowing users to search, access and analyze bioassay test results and metadata. In this work, we provide an update for the PubChem BioAssay resource, such as information content growth, new developments supporting data integration and search, and the recently deployed PubChem Upload to streamline chemical structure and bioassay submissions.


Expert Review of Proteomics | 2005

Histone structure and nucleosome stability

Leonardo Mariño-Ramírez; Maricel G. Kann; Benjamin A. Shoemaker; David Landsman

Histone proteins play essential structural and functional roles in the transition between active and inactive chromatin states. Although histones have a high degree of conservation due to constraints to maintain the overall structure of the nucleosomal octameric core, variants have evolved to assume diverse roles in gene regulation and epigenetic silencing. Histone variants, post-translational modifications and interactions with chromatin remodeling complexes influence DNA replication, transcription, repair and recombination. The authors review recent findings on the structure of chromatin that confirm previous interparticle interactions observed in crystal structures.


PLOS Computational Biology | 2009

Intrinsic Disorder in Protein Interactions: Insights From a Comprehensive Structural Analysis

Jessica H. Fong; Benjamin A. Shoemaker; Sergiy O. Garbuzynskiy; Michail Yu. Lobanov; Oxana V. Galzitskaya; Anna R. Panchenko

We perform a large-scale study of intrinsically disordered regions in proteins and protein complexes using a non-redundant set of hundreds of different protein complexes. In accordance with the conventional view that folding and binding are coupled, in many of our cases the disorder-to-order transition occurs upon complex formation and can be localized to binding interfaces. Moreover, analysis of disorder in protein complexes depicts a significant fraction of intrinsically disordered regions, with up to one third of all residues being disordered. We find that the disorder in homodimers, especially in symmetrical homodimers, is significantly higher than in heterodimers and offer an explanation for this interesting phenomenon. We argue that the mechanisms of regulation of binding specificity through disordered regions in complexes can be as common as for unbound monomeric proteins. The fascinating diversity of roles of disordered regions in various biological processes and protein oligomeric forms shown in our study may be a subject of future endeavors in this area.

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Anna R. Panchenko

National Institutes of Health

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Stephen H. Bryant

National Institutes of Health

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Manoj Tyagi

National Institutes of Health

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Thomas Madej

National Institutes of Health

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Paul A. Thiessen

National Institutes of Health

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Yanli Wang

National Institutes of Health

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Evan Bolton

National Institutes of Health

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Jiyao Wang

National Institutes of Health

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Ratna R. Thangudu

National Institutes of Health

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Siqian He

National Institutes of Health

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