Search Results for "algorithms"

...When it is impractical to use these methods to estimate a parameter, techniques can be used to optimize parameters so that model results best fit validation data. This tool was designed to optimize a user-specified list of parameters to a user-specified PBTK model. The user also controls validation data and optimization algorithms. In addition to optimized parameters, the tool outputs statistical information about the fit of the optimized model.

DEBay: Deconvolution of Ensemble through Bayes-approach DEBay estimates cell type-specific gene expression by deconvolution of quantitative PCR data of a mixed population. It will be useful in experiments where the segregation of different cell types in a sample is arduous, but the proportion of different cell types in the sample can be measured. DEBay uses the population distribution data and the qPCR data to calculate the relative expression of the target gene in different cell types in...

An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).

Phaistos is a framework for all-atom Monte Carlo simulations of proteins. It incorporates several advanced probabilistic models of protein structure for conformational sampling, efficient move-algorithms and the OPLS and PROFASI forcefields.

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. ExSTraCS was primarily developed to address problems in epidemiological data mining to identify complex patterns relating predictive attributes in noisy datasets to disease phenotypes of interest. ...

ChIP-RNA-seqPRO: A strategy for identifying regions of epigenetic deregulation associated with aberrant transcript splicing and RNA-editing sites. Runnable python scripts packaged together with customized annotation libraries, demo data input and README guide. 9/26 : v1.1 Updated MAIN_IV to debug error thrown by python pandas no longer supporting 'subset'. This code will no longer be actively maintained/updated here. A cloud-based resource for comparative analysis of epigenetic,...

The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.

StochPy - Stochastistic modeling in Python - is an easy-to-use package, which provides several stochastic simulation algorithms and unique analysis techniques, which can be used for stochastic simulations of biochemical systems.

...Additionally, all steps are tracked and can be reproduced later on. Xmipp is a well-known package in the EM image processing. It is integrated into Scipion and contains the algorithms in the core libraries and command line programs.

Genome coverage, the number of sequencing reads mapped to a position in a genome, is an insightful indicator of irregularities within sequencing experiments. While the average genome coverage is frequently used within algorithms in computational genomics, the complete information available in coverage profiles (i.e. histograms over all coverages) is currently not exploited to its full extent. Thus, biases such as fragmented or erroneous reference genomes often remain unaccounted for. Making this information accessible can improve the quality of sequencing experiments and quantitative analyses. ...

math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net

mitoMaker is a pipeline script developed to simplify the assembly and automatic annotation of mitochondrial genomes, based on raw NGS reads and an optional target reference. mitoMaker calls well known assemblers and algorithms, such as SOAPdenovo, MIRA and blast+ and parses their results providing easily readable outputs, such as FASTA, GENBANK, SEQUIN, PNG and others. General pipeline: 1-iterative De Novo assembly, with different k-mer values, trying to assemble a build that matches a target mitochondrial genome given. 2-searches for all mitochondrial gene features and circularization. 3-stores the best result found. 4-uses the best assembly as backbone for a reference based assembly, using MIRA and MITObim, trying to extend the mitogenome and close gaps. 5-annotates the best assembly, identifying the start and end position of each and every feature. 6-creates a folder with all the results (PNG, GENBANK, FASTA, SEQUIN, CAF, MAF and a stats logfile).

The Structural Proteomics Application Development Environment is a Python tool kit for developing and deploying bioinformatics applications. Handles graphics, analysis, and modeling of protein sequence and structure. Source and Win installers available. SPADE source code can be cloned from http://www.github.com/deaconjs/SPADE.

Cascading and Sharing Survival Trees (CSST) is a tree-based enseble that allows to efficiently analize survival data. It is a strightforward extension of the CS4 method for lifetime collections of data. The CSST software comes along with its companion the CSST Prediction tool, to use the ensemble prediction in everyday life. Please, refer to the user's manual for further information.

This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data.

...The Subversion repository was abandoned. """ E-Cell System is an object-oriented software suite for modeling, simulation, and analysis of large scale complex systems such as biological cells. It allows many components driven by multiple algorithms with different timescales to coexist in a model.

A univariate and multivariate analysis UI. This project is no longer under development. Please use as you wish.

MIVF - Medical Imaging and Visualization Factory, is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).

"Blue Planet" is a research project simulating the behaviour and darwinian evolution of unicellular lifeforms, each controlled by its own genetic program. Moreover, "Blue Planet Inhabitants" are suited for swarm intelligence and swarm research.

PARs is a bioinformatics tool for the analysis of cis-regulatory DNA sequences. Composed of two parts: a suite of sequence analysis algorithms for predicting cis-binding sites in DNA sequences and a GUI for visualisation and exploration of the results.

MetaPepSeq is metaserver for protein identification in Mass Spectrometry Experiments. It helps joining the power of Mascot and de novo sequencing algorithms by merging together into one tool.

A Java software for 3D visualization of graphs/networks. It implements many graph layout algorithms (such as force-directed methods), graph generators (such as scale-free networks) and graph modifiers. Most functions can be accessed through its GUI.

Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The

Solving genetic algorithms in a distributed processing system. Developed in python with sockets.

...These include the proportion of sequences with a gap, the level of residue similarity and, if several alignments for the same set of sequences are provided, the consistency level of columns among alignments. Moreover, trimAl allows to manually select a set of columns and sequences to be removed from the alignment. trimAl implements a series of automated algorithms that trim the alignment searching for optimum thresholds based on inherent characteristics of the input alignment, to be used so that the signal-to-noise ratio after alignment trimming phase is increased. Among trimAl’s additional features, trimAl allows getting the complementary alignment (columns that were trimmed), to compute statistics from the alignment, to select the output file format , to get a summary of trimAl’s trimming in HTML and SVG formats, and many other options.