Children: Bioinformatics
Darwin Core is a standard used for sharing and publishing biodiversity data. It provides a structured framework for the exchange of information related to biological diversity, including species occurrence data, taxonomic classifications, and other related environmental information. Darwin Core was created to improve the interoperability of biodiversity data across different systems and organizations. It consists of a set of terms and definitions, enabling biodiversity datasets to be easily shared and understood by researchers, conservationists, and policymakers globally.
The Darwin Core Archive (DwC Archive) is a data standard used for sharing biodiversity data. It is part of the Darwin Core standards, which provide a framework for providing information about biological diversity in a structured and interoperable way. The Darwin Core Archive facilitates the sharing and publishing of biodiversity datasets, particularly in the context of specimen records, observations, or related data concerning organisms. It consists of various types of metadata and data files that collectively allow for the easy exchange and usage of biodiversity information.
The DeLano Award for Computational Biosciences is an award that recognizes outstanding contributions and achievements in the field of computational biosciences. Named after Dr. Warren DeLano, a prominent scientist known for his work in molecular modeling and computational biology, the award commemorates innovative research and development that employs computational techniques to advance our understanding of biological systems and processes.
De novo protein structure prediction refers to the process of predicting the three-dimensional (3D) structure of a protein solely from its amino acid sequence, without using any information from homologous protein structures. This method relies on computational algorithms and models to simulate the physical and chemical principles governing protein folding, allowing researchers to make educated guesses about how a protein will fold into its functional form.
De novo transcriptome assembly is the process of reconstructing the complete set of RNA transcripts in a given organism or sample without prior reference to a known genome. This is particularly useful in situations where the genome of the organism is not available, poorly annotated, or when studying non-model organisms. Here are the key steps and concepts involved in de novo transcriptome assembly: 1. **RNA Extraction**: First, RNA is extracted from the cells or tissues of interest.
Demographic and Health Surveys (DHS) are extensive surveys that collect data on population, health, and nutrition indicators in developing countries. They are designed to provide high-quality and nationally representative data that are essential for policymakers, researchers, and program managers in the fields of public health, demographic studies, and development planning.
Digital phenotyping is a research method that involves the use of data collected from personal digital devices, such as smartphones, wearables, and other digital technologies, to assess and analyze an individual's behaviors, activities, and experiences. This approach aims to provide insights into an individual's health and well-being by capturing real-time, continuous data that reflects their psychological and physical states.
Digital transcriptome subtraction (DTS) is a computational technique used in bioinformatics and molecular biology to identify and differentiate between RNA transcripts that are present in a given sample. This method involves comparing the transcriptome of a particular sample against a reference transcriptome to subtract out unwanted or irrelevant transcripts, thereby highlighting specific transcripts of interest.
Direct Coupling Analysis (DCA) is a computational technique used in various fields such as biology, particularly in the analysis of protein structures and interactions, as well as in machine learning and statistics. In the context of protein science, DCA is used to identify and model the interactions between different residues in a protein sequence. The primary goal is to discern which amino acids are directly coupled to each other through evolutionary relationships.
The Distributed Annotation System (DAS) is a framework designed for the efficient integration and sharing of biological data, particularly annotations related to genomic features. DAS allows for the distribution and retrieval of biological data from multiple sources, enabling researchers to work with various datasets seamlessly. ### Key Components of DAS: 1. **Data Sources**: DAS servers host biological data and provide it through a standardized protocol. These servers can contain various types of data, including gene annotations, sequence information, and protein structures.
Do-it-yourself biology, often abbreviated as DIY biology or simply DIY bio, is a community-driven movement that encourages individuals and small groups to conduct biological research or experiments outside traditional academic and commercial labs. This grassroots approach democratizes access to biotechnology and biological experimentation, allowing hobbyists, students, and citizen scientists to explore biological concepts and innovate in various fields like genetics, microbiology, and synthetic biology.
Docking, in the context of molecular biology and chemistry, refers to a computational technique used to predict and analyze the interactions between two molecules, typically a small molecule (ligand) and a larger molecule, often a protein or nucleic acid (receptor). The primary objective of docking is to identify the preferred orientation and affinity of the ligand when it binds to the receptor, which can be crucial for drug discovery and development.
In bioinformatics, a dot plot is a graphical method used to visualize the similarities and differences between two biological sequences, such as DNA, RNA, or protein sequences. The primary purpose of a dot plot is to identify regions of similarity that may indicate homology, structural or functional relationships, or conserved sequences. ### How Dot Plots Work: 1. **Matrix Representation**: In a dot plot, one sequence is represented along the x-axis and the other along the y-axis.
A "dry lab" generally refers to a type of laboratory or research environment that focuses on computational and theoretical work rather than hands-on experimental work with physical materials. In a dry lab, researchers typically engage in activities such as: 1. **Computer Simulations**: Running simulations to model physical, chemical, biological, or engineering processes. 2. **Data Analysis**: Analyzing existing data sets, such as genomic data in bioinformatics or simulation results in physics.
A dual-flashlight plot is a visualization technique used in statistical analysis, particularly in the fields of genomics and bioinformatics. The term is often associated with the display of two-dimensional data sets, particularly in the context of visualizing relationships between variables or categories. In a dual-flashlight plot, two sets of data or two variables are represented on a two-dimensional axis, allowing for the comparison of their distributions, correlations, or other relationships.
The term "EMBRACE" can refer to a variety of things depending on the context. It could be an acronym for specific initiatives, programs, or terms in different fields, such as healthcare, education, or technology. For example, in healthcare, EMBRACE could refer to a specific program aimed at improving maternal and child health.
EVA, or Economic Value Added, is a financial performance metric that measures a company's ability to generate value above its cost of capital. It is often used as a benchmark to assess the profitability and efficiency of a company's operations. The concept was popularized by Stern Stewart & Co. in the 1990s.
Echinobase is a specialized database focused on echinoderm biology, providing a platform for researchers to access information about echinoderms, which include sea urchins, starfish, and sea cucumbers. The database typically includes genetic, genomic, and ecological data, as well as information about species distribution, developmental biology, and evolutionary relationships among echinoderms.
Engineering biology is an interdisciplinary field that combines principles of biology, engineering, and computational sciences to design and manipulate biological systems for various applications. It encompasses a broad range of activities, including the development of synthetic biological systems, the design of new organisms, and the manipulation of existing biological functions for practical uses. Key aspects of engineering biology include: 1. **Synthetic Biology**: This involves designing and constructing new biological parts, devices, and systems, as well as redesigning existing biological systems for useful purposes.