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Bioimage Informatics
Bioimage informatics is a subfield of bioinformatics and computational biology. It focuses on the use of computational techniques to analyze bioimages, especially cellular and molecular images, at large scale and high throughput. The goal is to obtain useful knowledge out of complicated and heterogeneous image and related metadata. Automated microscopes are able to collect large numbers of images with minimal intervention. This has led to a data explosion, which absolutely requires automatic processing. Additionally, and surprisingly, for several of these tasks, there is evidence that automated systems can perform better than humans. In addition, automated systems are unbiased, unlike human based analysis whose evaluation may (even unconsciously) be influenced by the desired outcome. There has been an increasing focus on developing novel image processing, computer vision, data mining, database and visualization techniques to extract, compare, search and manage the biological knowl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bioinformatics
Bioinformatics () is an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex. As an interdisciplinary field of science, bioinformatics combines biology, chemistry, physics, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data. Bioinformatics has been used for '' in silico'' analyses of biological queries using computational and statistical techniques. Bioinformatics includes biological studies that use computer programming as part of their methodology, as well as specific analysis "pipelines" that are repeatedly used, particularly in the field of genomics. Common uses of bioinformatics include the identification of candidates genes and single nucleotide polymorphisms (SNPs). Often, such identification is made with the aim to better understand the genetic basis of disease, unique adaptations, desirable properties (e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Histology
Histology, also known as microscopic anatomy or microanatomy, is the branch of biology which studies the microscopic anatomy of biological tissues. Histology is the microscopic counterpart to gross anatomy, which looks at larger structures visible without a microscope. Although one may divide microscopic anatomy into ''organology'', the study of organs, ''histology'', the study of tissues, and ''cytology'', the study of cells, modern usage places all of these topics under the field of histology. In medicine, histopathology is the branch of histology that includes the microscopic identification and study of diseased tissue. In the field of paleontology, the term paleohistology refers to the histology of fossil organisms. Biological tissues Animal tissue classification There are four basic types of animal tissues: muscle tissue, nervous tissue, connective tissue, and epithelial tissue. All animal tissues are considered to be subtypes of these four principal tissue types ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
RNAi
RNA interference (RNAi) is a biological process in which RNA molecules are involved in sequence-specific suppression of gene expression by double-stranded RNA, through translational or transcriptional repression. Historically, RNAi was known by other names, including ''co-suppression'', ''post-transcriptional gene silencing'' (PTGS), and ''quelling''. The detailed study of each of these seemingly different processes elucidated that the identity of these phenomena were all actually RNAi. Andrew Fire and Craig C. Mello shared the 2006 Nobel Prize in Physiology or Medicine for their work on RNAi in the nematode worm ''Caenorhabditis elegans'', which they published in 1998. Since the discovery of RNAi and its regulatory potentials, it has become evident that RNAi has immense potential in suppression of desired genes. RNAi is now known as precise, efficient, stable and better than antisense therapy for gene suppression. Antisense RNA produced intracellularly by an expression vector ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Small Molecules
Within the fields of molecular biology and pharmacology, a small molecule or micromolecule is a low molecular weight (≤ 1000 daltons) organic compound that may regulate a biological process, with a size on the order of 1 nm. Many drugs are small molecules; the terms are equivalent in the literature. Larger structures such as nucleic acids and proteins, and many polysaccharides are not small molecules, although their constituent monomers (ribo- or deoxyribonucleotides, amino acids, and monosaccharides, respectively) are often considered small molecules. Small molecules may be used as research tools to probe biological function as well as leads in the development of new therapeutic agents. Some can inhibit a specific function of a protein or disrupt protein–protein interactions. Pharmacology usually restricts the term "small molecule" to molecules that bind specific biological macromolecules and act as an effector, altering the activity or function of the target. Small mole ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
High-content Screening
High-content screening (HCS), also known as high-content analysis (HCA) or cellomics, is a method that is used in biological research and drug discovery to identify substances such as small molecules, peptides, or RNAi that alter the phenotype of a cell in a desired manner. Hence high content screening is a type of phenotypic screen conducted in cells involving the analysis of whole cells or components of cells with simultaneous readout of several parameters. HCS is related to high-throughput screening (HTS), in which thousands of compounds are tested in parallel for their activity in one or more biological assays, but involves assays of more complex cellular phenotypes as outputs. Phenotypic changes may include increases or decreases in the production of cellular products such as proteins and/or changes in the morphology (visual appearance) of the cell. Hence HCA typically involves automated microscopy and image analysis. Unlike high-content analysis, high-content screening implies ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automated Confocal Image Reader
Automation describes a wide range of technologies that reduce human intervention in processes, namely by predetermining decision criteria, subprocess relationships, and related actions, as well as embodying those predeterminations in machines. Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories, airplanes, and ships typically use combinations of all of these techniques. The benefit of automation includes labor savings, reducing waste, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision. Automation includes the use of various equipment and control systems such as machinery, processes in factories, boilers, and heat-treating ovens, switching on telephone networks, steering, and stabilization of ships, aircraft, and other applications and vehicles with reduced human inte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Co-occurrence Matrix
A co-occurrence matrix or co-occurrence distribution (also referred to as : ''gray-level co-occurrence matrices'' GLCMs) is a matrix that is defined over an image to be the distribution of co-occurring pixel values (grayscale values, or colors) at a given offset. It is used as an approach to texture analysis with various applications especially in medical image analysis. Method Given a grey-level image I, co-occurrence matrix computes how often pairs of pixels with a specific value and offset occur in the image. * The offset, (\Delta x, \Delta y), is a position operator that can be applied to any pixel in the image (ignoring edge effects): for instance, (1, 2) could indicate "one down, two right". * An image with p different pixel values will produce a p \times p co-occurrence matrix, for the given offset. * The (i, j)^\text value of the co-occurrence matrix gives the number of times in the image that the i^\text and j^\text pixel values occur in the relation given by the offse ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Feature Extraction
In machine learning, pattern recognition, and image processing, feature extraction starts from an initial set of measured data and builds derived values (features) intended to be informative and non-redundant, facilitating the subsequent learning and generalization steps, and in some cases leading to better human interpretations. Feature extraction is related to dimensionality reduction. When the input data to an algorithm is too large to be processed and it is suspected to be redundant (e.g. the same measurement in both feet and meters, or the repetitiveness of images presented as pixels), then it can be transformed into a reduced set of features (also named a feature vector). Determining a subset of the initial features is called feature selection. The selected features are expected to contain the relevant information from the input data, so that the desired task can be performed by using this reduced representation instead of the complete initial data. General Feature extractio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pattern Recognition
Pattern recognition is the automated recognition of patterns and regularities in data. It has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern recognition has its origins in statistics and engineering; some modern approaches to pattern recognition include the use of machine learning, due to the increased availability of big data and a new abundance of processing power. These activities can be viewed as two facets of the same field of application, and they have undergone substantial development over the past few decades. Pattern recognition systems are commonly trained from labeled "training" data. When no labeled data are available, other algorithms can be used to discover previously unknown patterns. KDD and data mining have a larger focus on unsupervised methods and stronger connection to business use. Pattern recognition focuses more on the s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Organelles
In cell biology, an organelle is a specialized subunit, usually within a cell, that has a specific function. The name ''organelle'' comes from the idea that these structures are parts of cells, as organs are to the body, hence ''organelle,'' the suffix ''-elle'' being a diminutive. Organelles are either separately enclosed within their own lipid bilayers (also called membrane-bound organelles) or are spatially distinct functional units without a surrounding lipid bilayer (non-membrane bound organelles). Although most organelles are functional units within cells, some function units that extend outside of cells are often termed organelles, such as cilia, the flagellum and archaellum, and the trichocyst. Organelles are identified by microscopy, and can also be purified by cell fractionation. There are many types of organelles, particularly in eukaryotic cells. They include structures that make up the endomembrane system (such as the nuclear envelope, endoplasmic reticulum, and Golg ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
