Children: Bioinformatics
Synthetic Biology Open Language (SBOL) is a standard for encoding information related to synthetic biology in a way that facilitates sharing and understanding across different platforms and tools. Introduced to improve interoperability in the field of synthetic biology, SBOL provides a structured framework for representing biological parts, devices, and systems, enabling researchers to effectively communicate about and reuse biological components.
Synthetic biology is an interdisciplinary field that combines principles from biology, engineering, and computer science to design and construct new biological parts, devices, and systems, or to re-engineer existing biological organisms for useful purposes. The aim of synthetic biology is to create innovative biological systems that can solve specific problems in areas such as medicine, agriculture, environmental sustainability, and biofuels.
Systems biology is an interdisciplinary field that focuses on the complex interactions within biological systems, integrating various biological data and approaches to understand the dynamics of these systems as a whole. Rather than studying individual components in isolation—such as genes, proteins, or metabolic pathways—systems biology seeks to understand how these components interact with each other and how they contribute to the overall behavior of biological organisms.
Systems biomedicine is an interdisciplinary field that combines principles from systems biology, medicine, and computational science to better understand biological systems and their relationship to health and disease. It integrates quantitative and qualitative approaches to analyze complex biological data, often utilizing high-throughput technologies such as genomics, proteomics, and metabolomics.
Systems immunology is an interdisciplinary field that integrates principles from immunology, systems biology, and computational modeling to understand the complex interactions within the immune system. It aims to analyze and characterize the immune response as a network of interactions among various components, such as cells, molecules, and pathways, rather than focusing on individual elements in isolation.
Template modeling score is a specific metric used in the context of protein structure prediction and modeling. It typically indicates the quality or accuracy of a model generated using a template, which is often based on known structures from databases like the Protein Data Bank (PDB). When creating a model using template modeling, researchers align a target sequence (the sequence of the protein being studied) with a known structure (the template) and predict the 3D structure of the target based on this alignment.
In the context of protein sequences, "threading" refers to a computational technique used in bioinformatics to predict protein structure based on known structures of other proteins. This method is particularly useful for proteins whose three-dimensional structures have not yet been determined experimentally. Here’s a brief overview of how threading works: 1. **Alignment with Known Structures**: Threading involves aligning a target protein sequence with a library of protein structures that have been previously solved (often referred to as a structure database).
As of my last knowledge update in October 2021, "TimeLogic" does not refer to a widely recognized term or concept in mainstream fields. However, there are a few possibilities that could relate to the term: 1. **Software or Technology**: TimeLogic could refer to specific software or tools used for time management, scheduling, or logical programming. Various companies may have products named "TimeLogic" that are focused on these areas.
"Toponome" is not a widely recognized term in common language, geography, or science up to my knowledge cutoff in October 2023. However, it might refer to various concepts depending on the context in which it's used, such as: 1. **Toponymy**: This is the study of place names (toponyms) and their origins, meanings, and use. It involves analyzing how geographic names reflect cultural, historical, and linguistic influences.
A **track hub** is a concept used primarily in the field of bioinformatics and genomics, specifically when working with data visualization and management in platforms like the UCSC Genome Browser. A track hub allows researchers to share and visualize various types of genomic data in a centralized manner. ### Key Features of Track Hubs: 1. **Data Sharing**: Track hubs enable the sharing of genomic data sets, such as gene annotations, variations, expressions, and other relevant biological information among researchers and institutions.
Transcription factor binding site databases are specialized repositories that catalog the binding sites of transcription factors (TFs) across various species and biological contexts. These databases are crucial for understanding gene regulation, as transcription factors are proteins that bind to specific DNA sequences to regulate the transcription of target genes. Here's a brief overview of what transcription factor binding site databases typically include: 1. **Data on Binding Sites**: They collect and curate information about the specific DNA sequences (binding sites) where transcription factors attach.
Translational research informatics is a field of study that focuses on the integration of data and information science with biomedical research to facilitate the translation of scientific discoveries into practical applications in healthcare. This discipline aims to bridge the gap between laboratory research (bench) and patient care (bedside) by utilizing informatics tools and methodologies to enhance the efficiency of the research process.
Translatomics is a branch of molecular biology that focuses on the study of the translation phase of gene expression, specifically the process by which messenger RNA (mRNA) is translated into proteins. This field encompasses the analysis of all aspects of translation, including the roles of ribosomes, transfer RNA (tRNA), amino acids, and various translation factors. In translatomics, researchers investigate how different factors can influence translation efficiency, fidelity, and regulation.
The UCSC Genome Browser is a web-based tool that provides access to a comprehensive set of genomic data and annotations for a variety of organisms, including humans and many model organisms. It is hosted by the University of California, Santa Cruz (UCSC) and is widely used by researchers in genomics, genetics, and molecular biology. The browser allows users to visualize and explore the genome sequences, gene annotations, regulatory elements, comparative genomics data, and other functional elements.
UniFrac is a distance metric used primarily in ecology and microbiome research to compare the phylogenetic diversity of communities. It is particularly useful for analyzing microbial communities by taking into account not just the presence or absence of different species, but also their evolutionary relationships. There are two main types of UniFrac: 1. **Weighted UniFrac**: This version considers the relative abundance of each species in the community.
UniProt, short for the Universal Protein Resource, is a comprehensive, high-quality database of protein sequence and functional information. It serves as a central hub for researchers in the fields of genomics, proteomics, and bioinformatics. UniProt is maintained by a consortium of organizations, primarily the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB), and the Protein Information Resource (PIR).
Unipept is a web-based platform designed for the analysis and interpretation of mass spectrometry-based peptide sequencing data. It provides tools for researchers to visualize and explore protein sequences, identify peptides, and understand their biological implications. Unipept allows users to input their mass spectrometry data, and it helps them identify proteins, visualize peptide occurrence and variability, and explore functional annotations.
The Vertebrate Genomes Project (VGP) is an ambitious scientific initiative aimed at producing high-quality, reference genome assemblies for the major vertebrate species on Earth. Launched to improve our understanding of vertebrate biology, evolution, and conservation, the project focuses on generating complete and accurate genomes using advanced sequencing technologies.
Viral metagenomics is a subfield of metagenomics that focuses specifically on the study of viral populations within environmental samples, organisms, or communities. It involves the use of high-throughput sequencing technologies to analyze a broad range of viral genomes present in a given sample, without the need for prior isolation and cultivation of the viruses.
Viroinformatics is an interdisciplinary field that combines virology, bioinformatics, and computational biology to analyze and interpret data related to viruses. It involves the use of computational tools and techniques to study viral genomes, viral evolution, and the interactions between viruses and their hosts. Key areas of focus in viroinformatics include: 1. **Genome Sequencing and Annotation**: Analyzing viral genomes to identify genetic features, such as coding regions, regulatory elements, and variants.