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ArrayTrack
ArrayTrack is a multi-purpose bioinformatics tool primarily used for microarray data management, analysis, and interpretation. ArrayTrack was developed to support in-house filter array research for the U.S. Food and Drug Administration in 2001 and was made freely available to the public as an integrated research tool for microarrays in 2003. Since then, ArrayTrack has averaged about 5,000 users per year. It is regularly updated by the National Center for Toxicological Research. Features ArrayTrack is composed of three major components: Study Database, Tools, and Libraries, which primarily handle data management, analysis, and interpretation, respectively. Each of these components can be directly accessed from the other two, e.g., analysis Tools can be used directly on experimental data stored in the Study Database, and significant genes discovered from the results can be queried in the Libraries to view additional annotations and associated proteins, pathways, Gene Ontology terms ...
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Food And Drug Administration (United States)
The United States Food and Drug Administration (FDA or US FDA) is a federal agency of the Department of Health and Human Services. The FDA is responsible for protecting and promoting public health through the control and supervision of food safety, tobacco products, caffeine products, dietary supplements, prescription and over-the-counter pharmaceutical drugs (medications), vaccines, biopharmaceuticals, blood transfusions, medical devices, electromagnetic radiation emitting devices (ERED), cosmetics, animal foods & feed and veterinary products. The FDA's primary focus is enforcement of the Federal Food, Drug, and Cosmetic Act (FD&C), but the agency also enforces other laws, notably Section 361 of the Public Health Service Act, as well as associated regulations. Much of this regulatory-enforcement work is not directly related to food or drugs, but involves such things as regulating lasers, cellular phones, and condoms, as well as control of disease in contexts varying fro ...
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Principal Component Analysis
Principal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data. Many studies use the first two principal components in order to plot the data in two dimensions and to visually identify clusters of closely related data points. Principal component analysis has applications in many fields such as population genetics, microbiome studies, and atmospheric science. The principal components of a collection of points in a real coordinate space are a sequence of p unit vectors, where th ...
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Macintosh
The Mac (known as Macintosh until 1999) is a family of personal computers designed and marketed by Apple Inc., Apple Inc. Macs are known for their ease of use and minimalist designs, and are popular among students, creative professionals, and software engineers. The current lineup includes the MacBook Air and MacBook Pro laptops, as well as the iMac, Mac Mini, Mac Studio and Mac Pro desktops. Macs run the macOS operating system. The Macintosh 128K, first Mac was released in 1984, and was advertised with the highly-acclaimed 1984 (advertisement), "1984" ad. After a period of initial success, the Mac languished in the 1990s, until co-founder Steve Jobs returned to Apple in 1997. Jobs oversaw the release of many successful products, unveiled the modern Mac OS X, completed the Mac transition to Intel processors, 2005-06 Intel transition, and brought features from the iPhone back to the Mac. During Tim Cook's tenure as CEO, the Mac underwent a period of neglect, but was later reinv ...
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Oracle Database
Oracle Database (commonly referred to as Oracle DBMS, Oracle Autonomous Database, or simply as Oracle) is a multi-model database management system produced and marketed by Oracle Corporation. It is a database commonly used for running online transaction processing (OLTP), data warehousing (DW) and mixed (OLTP & DW) database workloads. Oracle Database is available by several service providers on-prem, on-cloud, or as a hybrid cloud installation. It may be run on third party servers as well as on Oracle hardware (Exadata on-prem, on Oracle Cloud or at Cloud at Customer). History Larry Ellison and his two friends and former co-workers, Bob Miner and Ed Oates, started a consultancy called Software Development Laboratories (SDL) in 1977. SDL developed the original version of the Oracle software. The name ''Oracle'' comes from the code-name of a CIA-funded project Ellison had worked on while formerly employed by Ampex. Releases and versions Oracle products follow a custom r ...
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Single-nucleotide Polymorphism
In genetics, a single-nucleotide polymorphism (SNP ; plural SNPs ) is a germline substitution of a single nucleotide at a specific position in the genome. Although certain definitions require the substitution to be present in a sufficiently large fraction of the population (e.g. 1% or more), many publications do not apply such a frequency threshold. For example, at a specific base position in the human genome, the G nucleotide may appear in most individuals, but in a minority of individuals, the position is occupied by an A. This means that there is a SNP at this specific position, and the two possible nucleotide variations – G or A – are said to be the alleles for this specific position. SNPs pinpoint differences in our susceptibility to a wide range of diseases, for example age-related macular degeneration (a common SNP in the CFH gene is associated with increased risk of the disease) or nonalcoholic fatty liver disease (a SNP in the PNPLA3 gene is associated with inc ...
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Chemical Compound
A chemical compound is a chemical substance composed of many identical molecules (or molecular entities) containing atoms from more than one chemical element held together by chemical bonds. A molecule consisting of atoms of only one element is therefore not a compound. A compound can be transformed into a different substance by a chemical reaction, which may involve interactions with other substances. In this process, bonds between atoms may be broken and/or new bonds formed. There are four major types of compounds, distinguished by how the constituent atoms are bonded together. Molecular compounds are held together by covalent bonds; ionic compounds are held together by ionic bonds; intermetallic compounds are held together by metallic bonds; coordination complexes are held together by coordinate covalent bonds. Non-stoichiometric compounds form a disputed marginal case. A chemical formula specifies the number of atoms of each element in a compound molecule, using the s ...
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Gene Ontology
The Gene Ontology (GO) is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species. More specifically, the project aims to: 1) maintain and develop its controlled vocabulary of gene and gene product attributes; 2) annotate genes and gene products, and assimilate and disseminate annotation data; and 3) provide tools for easy access to all aspects of the data provided by the project, and to enable functional interpretation of experimental data using the GO, for example via enrichment analysis. GO is part of a larger classification effort, the Open Biomedical Ontologies, being one of the Initial Candidate Members of the OBO Foundry. Whereas gene nomenclature focuses on gene and gene products, the Gene Ontology focuses on the function of the genes and gene products. The GO also extends the effort by using markup language to make the data (not only of the genes and their products but also of curated attributes) machine read ...
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Protein
Proteins are large biomolecules and macromolecules that comprise one or more long chains of amino acid residues. Proteins perform a vast array of functions within organisms, including catalysing metabolic reactions, DNA replication, responding to stimuli, providing structure to cells and organisms, and transporting molecules from one location to another. Proteins differ from one another primarily in their sequence of amino acids, which is dictated by the nucleotide sequence of their genes, and which usually results in protein folding into a specific 3D structure that determines its activity. A linear chain of amino acid residues is called a polypeptide. A protein contains at least one long polypeptide. Short polypeptides, containing less than 20–30 residues, are rarely considered to be proteins and are commonly called peptides. The individual amino acid residues are bonded together by peptide bonds and adjacent amino acid residues. The sequence of amino acid residue ...
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Gene
In biology, the word gene (from , ; "...Wilhelm Johannsen coined the word gene to describe the Mendelian units of heredity..." meaning ''generation'' or ''birth'' or ''gender'') can have several different meanings. The Mendelian gene is a basic unit of heredity and the molecular gene is a sequence of nucleotides in DNA that is transcribed to produce a functional RNA. There are two types of molecular genes: protein-coding genes and noncoding genes. During gene expression, the DNA is first copied into RNA. The RNA can be directly functional or be the intermediate template for a protein that performs a function. The transmission of genes to an organism's offspring is the basis of the inheritance of phenotypic traits. These genes make up different DNA sequences called genotypes. Genotypes along with environmental and developmental factors determine what the phenotypes will be. Most biological traits are under the influence of polygenes (many different genes) as well as gen ...
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Linear Discriminant Analysis
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification. LDA is closely related to analysis of variance (ANOVA) and regression analysis, which also attempt to express one dependent variable as a linear combination of other features or measurements. However, ANOVA uses categorical independent variables and a continuous dependent variable, whereas discriminant analysis has continuous independent variables and a categorical dependent variable (''i.e.'' the class label). Logistic regression and probit regression are more similar to LDA than ANOVA is, as they also explain a categorical var ...
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K-nearest Neighbors Algorithm
In statistics, the ''k''-nearest neighbors algorithm (''k''-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, and later expanded by Thomas Cover. It is used for classification and regression. In both cases, the input consists of the ''k'' closest training examples in a data set. The output depends on whether ''k''-NN is used for classification or regression: :* In ''k-NN classification'', the output is a class membership. An object is classified by a plurality vote of its neighbors, with the object being assigned to the class most common among its ''k'' nearest neighbors (''k'' is a positive integer, typically small). If ''k'' = 1, then the object is simply assigned to the class of that single nearest neighbor. :* In ''k-NN regression'', the output is the property value for the object. This value is the average of the values of ''k'' nearest neighbors. If ''k'' = 1, then the output is simply assigned to the v ...
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Hierarchical Clustering
In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two categories: * Agglomerative: This is a " bottom-up" approach: Each observation starts in its own cluster, and pairs of clusters are merged as one moves up the hierarchy. * Divisive: This is a "top-down" approach: All observations start in one cluster, and splits are performed recursively as one moves down the hierarchy. In general, the merges and splits are determined in a greedy manner. The results of hierarchical clustering are usually presented in a dendrogram. The standard algorithm for hierarchical agglomerative clustering (HAC) has a time complexity of \mathcal(n^3) and requires \Omega(n^2) memory, which makes it too slow for even medium data sets. However, for some special cases, optimal efficient agglomerative methods (of c ...
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