Search Results for "mining" - Page 7
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Showing 461 open source projects for "mining"
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This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
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GNAT
GNAT recognizes gene names in text and maps them to NCBI Entrez Gene
GNAT is a BioNLP/text mining tool to recognize and identify gene/protein names in natural language text. It will detect mentions of genes in text, such as PubMed/Medline abstracts, and disambiguate them to remove false positives and map them to the correct entry in the NCBI Entrez Gene database by gene ID. March 2017: We started to upload GNAT output on Medline. -
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Chronological Cohesive Units
The experimental source code for the paper
The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming" -
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wgssat_nbfgr
WGSSAT: SSR Annotation Pipeline
...This pipeline integrates prediction of genes, ncRNA, repeats and SSR from whole genome assembly and mapping of these predicted SSR on to the genome (classified according to genes, ncRNA, repeats, exonic and intronic region) along with primer designing and mining of cross-species amplification markers. The mining of SSRs from whole genome provides valuable information on the abundance of SSRs in various genomic regions and will also facilitate the development of markers for genetic analysis and related applications, such as marker-assisted breeding and linkage mapping. -
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CUBiBit
Tool to search binary biclusters on CUDA-enabled GPUs
CUBiBit is a parallel tool to accelerate the search of biclusters on binary datasets using CUDA-enabled GPUs. This data mining procedure is especially useful for gene expression data. This tool receives as input a file with ARFF extension that contais the binary values of m attributes and n samples and returns a file with the biclustering information. It is able to exploit the parallel capabilities of manycore NVIDIA GPUS. It also makes use of C++11 multithreading support to accelerate one phase of the algorithm on several CPU cores. -
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BioRec:Bird Census field data annotation
Recognizing biological data from a notebook.
This project helps to digitize field data for a certain Bird Census method. Namely, bird census based on personal inspection or small (~10 km^2) regions with recording birds' position and behaviour on paper. This project makes it easy to annotate such field data and to make this data available for statistical analysis. -
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Bytecoin (BCN)
Bytecoin is a cryptocurrency based on the unique CryptoNote technology
Bytecoin (BCN) is a cryptocurrency developed from scratch and based on the unique CryptoNote technology. Bytecoin provides its users with high level of privacy protection and true democratic way of mining. Main features of BCN are: - untraceable and unlinkable transactions, - egalitarian PoW, - analysis resistant blockchain. It's also designed to be easy mined on average PC. BCN brings equality to all miners and users. Bytecoin (BCN) was launched on July 4, 2012. -
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Bolt ML
10x faster matrix and vector operations
Bolt is an open-source research project focused on accelerating machine learning and data mining workloads through efficient vector compression and approximate computation techniques. The core idea behind Bolt is to compress large collections of dense numeric vectors and perform mathematical operations directly on the compressed representations instead of decompressing them first. This approach significantly reduces both memory usage and computational overhead when working with high-dimensional data commonly used in machine learning systems. ... -
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In-Close
In-Close is a fast Formal Concept miner.
In-Close is a fast Formal Concept Miner and Tree Builder for FCA files in the cxt format and FIMI .dat files. Features include: minimum support for intent and extent, output of analysis data, output of concepts, output of reduced context using minimum support values and output of sorted cxt file (thus can convert dat to cxt format). -
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MYRA
A collection of ACO algorithms for the data mining classification task
MYRA is a collection of Ant Colony Optimization (ACO) algorithms for the data mining classification task. It includes popular rule induction and decision tree induction algorithms. The algorithms are ready to be used from the command line or can be easily called from your own Java code. They are build using a modular architecture, so they can be easily extended to incorporate different procedures and/or use different parameter values. -
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SPAWNN
SPatial Analysis With self-organizing Neural Networks
The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining. To run the toolkit, simply download and execute (double-click) the jar-file. Please cite: - Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775. Other related publications: - Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. ... -
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PyDaMelo
Python-compatible Data mining elementary objects
An attempt at offering machine learning and data mining algorithms at the finest grain we are able to, easy to combine together through Python scripting to glue together the Lego-like bricks. -
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All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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nheqminer
Equihash miner for NiceHash
nheqminer is the Equihash miner for NiceHash, an advanced crypto currency cloud mining, hash rental service and multipool. Builds are currently available for Windows and in progress for Linux. -
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Lattice Miner is a data mining prototype for creating, visualizing and exploring concept (Galois) lattices. It allows the generation of formal concepts and association rules.
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BISD
Batch incremental SNN-DBSCAN clustering algorithm
Incremental data mining algorithms process frequent up- dates to dynamic datasets efficiently by avoiding redundant computa- tion. Existing incremental extension to shared nearest neighbor density based clustering (SNND) algorithm cannot handle deletions to dataset and handles insertions only one point at a time. We present an incremen- tal algorithm to overcome both these bottlenecks by efficiently identify- ing affected parts of clusters while processing updates to dataset in batch mode. -
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MOGEN
The software for modeling the 3D structure of a genome using Hi-C data
...Detail on how to use it: https://github.com/BDM-Lab/MOGEN It is published in Bioinformatics: http://bioinformatics.oxfordjournals.org/content/32/9/1286 Bioinformatics, Data Mining, Machine Learning (BDM) Laboratory, Jianlin Cheng, PhD Department of Computer Science University of Missouri, Columbia Email: chengji@missouri.edu -
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GAKNN is a data mining software for gene annotation data. GAKNN is built with k- Nearest Neighbour algorithm optimized by the genetic algorithm. Gene annotation datasets saved under .csv or .arff formats with Gene Ontology or FunCat categorization can use GAKNN to predict gene functions.
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data... -
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LorDG
3D genome reconstruction with Lorentzian objective function
...Detail on how to use it: https://github.com/BDM-Lab/Lordg It is published in Nucleic Acids Research : http://nar.oxfordjournals.org/content/early/2016/11/29/nar.gkw1155.long Bioinformatics, Data Mining, Machine Learning (BDM) Laboratory, Jianlin Cheng, PhD Department of Computer Science University of Missouri, Columbia Email: chengji@missouri.edu -
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EpiMINE
program for mining epigenomic data
EpiMINE is a program designed for mining epigenomic data. This application performs genome wide based quantitative and correlative analysis between different annotated or raw chip-seq like datasets in the regions of interest (RI). Apart from this the tool takes the advantage in linking results with expression data. It is available both in graphical user interface and in command line form. -
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Kohonen neural network library is a set of classes and functions for design, train and use Kohonen network (self organizing map) which is one of AI algorithms and useful tool for data mining and discovery knowledge in data (http://knnl.sf.net).
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Molecular Simulation Grid
Provides high performance computing power and state of the art tools
MoSGrid focuses on the configuration and provision of Grid services for molecular simulations and annotation of the results with metadata and their provision for data mining and knowledge generation. It is based on Liferay technology togethe with gUSE. -
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iCubing
Several OLAP algorithms, data structures and HPC OLAP versions
OLAP technology is very useful for decision makers and data mining tools with BIG data. In this direction, we implement iCubing project with several multidimensional data cube approaches for cube indexing, querying, updating and mining. There are also several cube types, i.e. alphanumeric cubes, text cubes with unstructured data and geo cube with geo types, dimensions, measures and hierarchies, so the OLAP area continues a hard challenge after more than 20 years of the seminal paper of Jim Gray et al. in 1997. ... -
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JaCa-DDM
DDM powered by the JaCa model
JaCa-DDM is a novel agent-based Distributed Data Mining system founded on the Agents & Artifacts paradigm, conceived to design, implement, deploy, and evaluate distributed learning strategies.
