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The McDonald–Kreitman test [1] is a statistical test often used by evolutionary and population biologists to detect and measure the amount of adaptive evolution within a species by determining whether adaptive evolution has occurred, and the proportion of substitutions that resulted from positive selection (also known as directional selection).
Sorted into folders by class of events as well as metadata in a JSON file and annotations in a CSV file. 1,059 Sound Classification 2014 [146] [147] J. Salamon et al. AudioSet 10-second sound snippets from YouTube videos, and an ontology of over 500 labels. 128-d PCA'd VGG-ish features every 1 second. 2,084,320
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
The International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology announce the 10th ISCB Student Wikipedia Competition: the competition aims to improve Wikipedia's coverage of any topic relating to ISCB's Bioinformatics Core Competencies (see table to the right).
Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).
Open data may include non-textual material such as maps, genomes, connectomes, chemical compounds, mathematical and scientific formulae, medical data, and practice, bioscience and biodiversity data. A major barrier to the open data movement is the commercial value of data.
The goal of learning in the self-organizing map is to cause different parts of the network to respond similarly to certain input patterns. This is partly motivated by how visual, auditory or other sensory information is handled in separate parts of the cerebral cortex in the human brain.
Scatterplot of the data set. The Iris flower data set or Fisher's Iris data set is a multivariate data set used and made famous by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis. [1]