Search Results for "lotto prediction algorithm" - Page 2
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Showing 40 open source projects for "lotto prediction algorithm"
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PSICOV
The unofficial binary for PSICOV: Protein Sparse Inverse COVariance
PSICOV (Protein Sparse Inverse Covariance estimation program) is a coevoultion algorithm applied to very large (typically >=1000 sequences) multiple sequence alignments for precise protein structural contact prediction. This is the unofficial precompiled Windows binary for PSICOV compiled by Chengxin Zhang at Fudan University. The source code is copyrighted by David T. Jones, University College London. -
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BiRW
Bi-random Walks for Phenome-Genome Association Prediction
The availability of ontologies and systematic documentations of phenotypes and their genetic associations has enabled large-scale network-based global analyses of the association between the complete collection of phenotypes (phenome) and genes. BiRW is a package designed for analysis and prediction of the phenome-genome associations. BiRW package contains a program for analysis of circular bigraphs (CBGs) and the bi-random walk (BiRW) algorithm to capture the CBG patterns in the networks for unveiling human and mouse phenome-genome association. The processed OMIM human disease phenotype-gene association network and MGI mouse phentoype-gene association network are also released together with the source code. -
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CNVision
CNV prediction from Illumina genotyping data
CNVision is a Perl script that runs Illumina genotyping data (all chips from 300k to latest Omni) through PennCNV, QuantiSNPv2.3 and GNOSIS (an in-built algorithm). It merges the results and assesses the quality of the raw data. CNVision can also identify de novo CNVs in family-based data using a highly accurate algorithm that considers the possibility of CNVs in either parent based on the raw genotyping data. The script is optimized to work in a UNIX-based environment; it should work in... -
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. -
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Unsupervised Random Forest
On-line Unsupervised Random Forest
This tool uses Random Forest and PAM to cluster observations and to calculate the dissimilarity between observations. It supports on-line prediction of new observations (no need to retrain); and supports datasets that contain both continuous (e.g. CPU load) and categorical (e.g. VM instance type) features. In particular, we use an unsupervised formulation of the Random Forest algorithm to calculate similarities and provide them as input to a clustering algorithm. For the sake of efficiency and meeting the dynamism requirement of autonomic clouds, our methodology consists of two steps: (i) off-line clustering and (ii) on-line prediction. ... -
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Neural Libs
Neural network library for developers
This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network. -
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DeNovoCheck
DeNovoCheck: Inheritance analysis for NGS trio data
DeNovoCheck is intended to be used for inheritance analysis in NGS tio data. For rare dominant Mendelian diseases, patient-parent trios are often used to reduce the number of candidate variants. The algorithm bases the inheritance prediction on the data available in the parental BAM files and allows for a fast and reliable selection of potential de novo variants. -
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GSP program are based on Bayesian framework with an EM algorithm to predict genome size iteratively, which is elegant in mathematics. The model first develop under the no sequencing error model, then extend to the sequencing errors containing model.
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BayesianCortex
simple algorithm for a realtime interactive visual cortex for painting
A paint program where the canvas is the visual cortex of a simple kind of artificial intelligence. You paint with the mouse into its dreams and it responds by changing what you painted gradually. There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be... -
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This project applies an interpretation of a k-NN algorithm to a library of GPS commuter data for speed prediction. The overall goal is to lay the foundation for a power management protocol for use in electric vehicles with hybrid energy storage.
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Identification of biological species via iterational process of giving an ordered set of questions to user. The order is defined by an optimization algorithm, trying to provide the most correct prediction about the questions to ask.
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Shape is a molecular conformation prediction program. It uses a genetic algorithm to efficiently search the conformational space of a biomolecule and then clusters the results. It is very simple to use.
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The TMpred program makes a prediction of membrane-spanning regions and their orientation. The algorithm is based on the statistical analysis of TMbase, a database of naturally occuring transmembrane proteins.
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segmentation-fold
Youri Hoogstrate's RNA folding (2D structure prediction) algorithm
https://github.com/yhoogstrate/segmentation-fold/
