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Topic Review
List of Protein Subcellular Localization Prediction Tools
This list of protein subcellular localisation prediction tools includes software, databases, and web services that are used for protein subcellular localization prediction. Some tools are included that are commonly used to infer location through predicted structural properties, such as signal peptide or transmembrane helices, and these tools output predictions of these features rather than specific locations. These software related to protein structure prediction may also appear in lists of protein structure prediction software.
  • 1.3K
  • 18 Oct 2022
Topic Review
Circle-ellipse Problem
The circle-ellipse problem in software development (sometimes termed the square-rectangle problem) illustrates several pitfalls which can arise when using subtype polymorphism in object modelling. The issues are most commonly encountered when using object-oriented programming (OOP). By definition, this problem is a violation of the Liskov substitution principle, one of the SOLID principles. The problem concerns which subtyping or inheritance relationship should exist between classes which represent circles and ellipses (or, similarly, squares and rectangles). More generally, the problem illustrates the difficulties which can occur when a base class contains methods which mutate an object in a manner which may invalidate a (stronger) invariant found in a derived class, causing the Liskov substitution principle to be violated. The existence of the circle-ellipse problem is sometimes used to criticize object-oriented programming. It may also imply that hierarchical taxonomies are difficult to make universal, implying that situational classification systems may be more practical.
  • 229
  • 18 Oct 2022
Topic Review
Moz (Marketing Software)
Moz is a software as a service (SaaS) company based in Seattle that sells inbound marketing and marketing analytics software subscriptions. It was founded by Rand Fishkin and Gillian Muessig in 2004 as a consulting firm and shifted to SEO software development in 2008. The company hosts a website that includes an online community of more than one million globally based digital marketers and marketing related tools. Moz offers SEO tools that includes keyword research, link building, site audits, and page optimization insights in order to help companies to have a better view of the position they have on search engines and how to improve their ranking. The company also developed the most commonly used algorithm to determine Domain Authority, which is a score between 1-100, that is often used by many SEO companies to estimate a website's overall viability with the search engines.
  • 1.8K
  • 18 Oct 2022
Topic Review
Scientific Community Metaphor
In computer science, the scientific community metaphor is a metaphor used to aid understanding scientific communities. The first publications on the scientific community metaphor in 1981 and 1982 involved the development of a programming language named Ether that invoked procedural plans to process goals and assertions concurrently by dynamically creating new rules during program execution. Ether also addressed issues of conflict and contradiction with multiple sources of knowledge and multiple viewpoints.
  • 230
  • 18 Oct 2022
Topic Review
HandWiki
HandWiki is an internet Wiki-style encyclopedia for professional researchers in various branches of science and computer science. As other Wiki type encyclopedias, HandWiki is designed for collaborative editing of articles. Unlike the traditional Wikipedia that uses the categories concept for all articles located in the main namespace, HandWiki uses dedicated namespaces for each topic. This allows creation of "Books" or "Manual" by grouping articles under the same namespace. According to the Handwiki designers, this can simplify organization of articles according to particular topic. HandWiki has the following topics included in the dedicated namespaces: Mathematics, Computers, Analysis, Physics, Astronomy, Biology, Chemistry, Unsolved. In addition to the categories preserved from Wikipedia, HandWiki has its own categories for original articles posted to HandWiki. One notable feature of HandWiki is that it allows to collaborate in real-time on many types of documents (lectures, books, technical documents, etc.) with multiple authors. The text can be protected from viewing, and can only be available for groups of people working on the same project. HandWiki can be used to convert such articles to LaTeX and to use BibTeX for referencing. These two features are a significant advantage for preparing research articles for publication. The HandWiki is designed using the MediaWiki software with additional extensions for inclusion of references to programming codes and BibTeX citations. Handwiki allows adding advertisements to the end of the articles. The advertising icons can be grouped according to the HandWiki topics.
  • 6.7K
  • 18 Oct 2022
Topic Review
FireEye
FireEye is a privately held cybersecurity company headquartered in Milpitas, California. It has been involved in the detection and prevention of major cyber attacks. It provides hardware, software, and services to investigate cybersecurity attacks, protect against malicious software, and analyze IT security risks. FireEye was founded in 2004. Initially, it focused on developing virtual machines that would download and test internet traffic before transferring it to a corporate or government network. The company diversified over time, in part through acquisitions. In 2014, it acquired Mandiant, which provides incident response services following the identification of a security breach. FireEye went public in 2013. USAToday says FireEye "has been called in to investigate high-profile attacks against Target, JP Morgan Chase, Sony Pictures, Anthem and others".
  • 1.4K
  • 18 Oct 2022
Topic Review
Modo
Modo (stylized as MODO, and originally modo) is a polygon and subdivision surface modeling, sculpting, 3D painting, animation and rendering package developed by Luxology, LLC, which is now merged with and known as Foundry. The program incorporates features such as n-gons and edge weighting, and runs on Microsoft Windows, Linux and macOS platforms.
  • 821
  • 18 Oct 2022
Topic Review
Winograd Schema Challenge
The Winograd schema challenge (WSC) is a test of machine intelligence proposed by Hector Levesque, a computer scientist at the University of Toronto. Designed to be an improvement on the Turing test, it is a multiple-choice test that employs questions of a very specific structure: they are instances of what are called Winograd schemas, named after Terry Winograd, professor of computer science at Stanford University. On the surface, Winograd schema questions simply require the resolution of anaphora: the machine must identify the antecedent of an ambiguous pronoun in a statement. This makes it a task of natural language processing, but Levesque argues that for Winograd schemas, the task requires the use of knowledge and commonsense reasoning. Nuance Communications announced in July 2014 that it would sponsor an annual WSC competition, with a prize of $25,000 for the best system that could match human performance. However, the prize is no longer offered.
  • 384
  • 18 Oct 2022
Topic Review
TScript
TScript is an object-oriented embeddable scripting language for C++ that supports hierarchical transient typed variables (TVariable). Its main design criterion is to create a scripting language that can interface with C++, transforming data and returning the result. This enables C++ applications to change their functionality after installation.
  • 411
  • 18 Oct 2022
Topic Review
Computer-Aided Diagnosis Approach for Breast Cancer
Breast cancer is a gigantic burden on humanity, causing the loss of enormous numbers of lives and amounts of money. It is the world’s leading type of cancer among women and a leading cause of mortality and morbidity. The histopathological examination of breast tissue biopsies is the gold standard for diagnosis. A computer-aided diagnosis (CAD) system based on deep learning is developed to ease the pathologist’s mission A new transfer learning approach is introduced for breast cancer classification using a set of pre-trained Convolutional Neural Network (CNN) models with the help of data augmentation techniques. Multiple experiments are performed to analyze the performance of these pre-trained CNN models through carrying out magnification dependent and magnification independent binary and eight-class classifications. Xception model has shown a promising performance through achieving the highest classification accuracy for all experiments.
  • 393
  • 17 Oct 2022
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