A computer algorithm that identifies similar protein 3-dimensional structures. Structure neighbors for every structure in MMDB are pre-computed and accessible via links on the MMDB Structure Summary pages.

The Protein database is a collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB. Protein sequences are the fundamental determinants of biological structure and function.

A stand-alone application for viewing 3-dimensional structures from NCBI Entrez retrieval service. Runs on Windows, Macintosh, and UNIX and can be configured to receive data from most popular Web browsers.

This repository provides the raw data and analysis code used to demonstrate the implementation of a mathematical framework that uses internal standards to correct for compositionally in MGS datasets. Some of the data contained herein was previously published and is reanalyzed in the context of this new framework, while other datasets represent newly analyzed samples. Please refer to the associated publication for further discussion and a full exploration of the results.

The Nucleotide database is a collection of sequences from several sources, including GenBank, RefSeq, TPA and PDB. Genome, gene and transcript sequence data provide the foundation for biomedical research and discovery.

The BioSample database contains descriptions of biological source materials used in experimental assays.

CDTree is a stand-alone application for classifying protein sequences and investigating their evolutionary relationships. CDTree can import, analyze and update existing Conserved Domain (CDD) records and hierarchies, and also allows users to create their own.

An interactive Web application that enables users to visualize multiple alignments created by database search results or other software applications. The MSA Viewer allows users to upload an alignment and set a master sequence and to explore the data using features such as zooming and changing of coloration.

Additional details used in the methods are found in the MS Word file “S1_Dawson et al._Supporting_Information.docx”. The MS Excel file “S2_Dawson et al. Supporting Information.xlsx” contains datasets and graphical results. The Excel file sheets are as follows: S2.1 illustrates Clint hepatic flow calculations, S2.2 - 5 include training and test data sets; S2.6-7 include figures illustrating Clint model selection criteria and assemblages of model descriptors; S2.8 includes confusion matrices for evaluation Clint model, S2.9-10 include figures illustrating fup model selection criteria and assemblages of model descriptors (with ranges); S2.11 includes tables of model assessments of the Clint test set, S2.12 includes information relevant to BER calculations for the ToxCast test set, S2.13 includes information relevant to BER calculations for Tox21 chemicals, and S2.14 provides information on different transformations for fup. This dataset is associated with the following publication: Dawson, D., B. Ingle, K. Phillips, J. Nichols, J. Wambaugh, and R. Tornero-Velez. Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 55(9): 6505, (6517).