Search Results for "algorithm"
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Showing 73 open source projects for "algorithm"
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miRDeep*
MiRDeep*
Please cite: An, J., Lai, J., Lehman, M.L. and Nelson, C.C. (2013) miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data. Nucleic Acids Res, 41, 727-737. We will create index for you if you tell us your interested species (j.an@qut.edu.au). download command line version "MDS_command_line_Vxx.zip" clicking "Browse All Files" please find miRPlant in sourceforge for plant miRNA prediction. -
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BD-Func
Bidirectional Functional Enrichment of Gene Expression Data
BD-Func is an algorithm to predict activation or inhibition of pathways based upon gene expression patterns. If you use BD-Func, please cite: Warden C, Kanaya N, Chen S, and Yuan Y-C. (2013) BD-Func: A Streamlined Algorithm for Predicting Activation and Inhibition of Pathways. peerJ, 1:e159 -
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MAGeCK
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support... -
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The Kinetic Simulation Algorithm Ontology (KiSAO; http://co.mbine.org/standards/kisao) is an ontology of algorithms for simulating and analyzing biological models, as well as the characteristics of these algorithms, their input parameters, and their outputs. In addition, KiSAO captures relationships among algorithms, their parameters, and their outputs. Development of KiSAO has moved to https://github.com/SED-ML/KiSAO/.
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ModST
A tool to search post-translational modifications in a blind mode
ModST (pronounced as modest) is a tool to search post-translational modifications (PTMs) in mass spectrometry data in an unrestrictive manner. It can search for hundreds of modification without any user provided information for variable modifications. Due to data level parallelization implemented through perl it is fast, portable and easy to use to identify and analyse PTMs in MS/MS data. -
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COHCAP
City of Hope CpG Island Analysis Pipeline
COHCAP (City of Hope CpG Island Analysis Pipeline, pronounced "co-cap") is an algorithm to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). Please note: 1) The SourceForge version of COHCAP is no longer being updated. Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub. 2) In addition to the original NAR paper, please see the following links: Benchmarks: http://www.nature.com/protocolexchange/protocols/2965#/introduction Protocol Exchange Files: http://sourceforge.net/projects/cohcap/files/Protocol_Exchange_Example.zip 3) Custom Annotation Files (including EPIC Array): https://sourceforge.net/projects/cohcap/files/additional_Bioconductor_annotations.zip/download -
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MORPHEUS for Fiji
A tool for unbiased and reproducible cell morphometry in Fiji/ImageJ2
...Specifically, MORPHEUS works with sampling distributions to learn—in an unsupervised manner and by a non-parametric approach—how to recognize the cells suitable for subsequent analysis. Afterwards, the algorithm performs the evaluation of the most relevant cell-shape descriptors over the full set of detected cells. Optionally, also the extraction of nucleus features and a double-scale analysis of orientation can be performed. The whole algorithm is implemented as a one-click procedure, thus minimizing the user intervention and the ensuing biases and errors of human origin. ... -
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DACO-algorithm
A novel transcription factor complex prediction algorithm.
...Complexation of transcription factors and other regulatory proteins is a prevailing and highly conserved mechanism of signal integration within critical regulatory pathways and enable to infer controlled genes as well as the exerted regulatory mechanism. We developed DACO (domain-aware cohesiveness optimization), a novel algorithm that combines protein-protein interaction networks and domain-domain interaction networks with the cluster-quality metric cohesiveness. The metric is locally maximized on the holistic level of protein interactions while sophisticated connectivity constraints on the domain level are utilized to account for the exclusive and thus inherently combinatorial nature of the interactions within such assemblies. ... -
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The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. ...
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De_Lux
Deconvolution of luminescence cross-talk in microplate reader data
An algorithm to deconvolve the luminescence cross-talk in high-throughput gene expression profiling to recover the true luminescence activity of a microplate. -
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JSiteDescriptor
Binding site descriptor generation for SVM based classification.
A set of java programs that extract coordinate and chemical information from PDB files. The binding site regions are extracted using grid based scheme. For binding site, spatio-chemical descriptor is generated based on PocketMatch algorithm of Dr. Kalidas (author of this project too). -
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D-Tailor
D-Tailor: automated analysis and design of DNA sequences
...DNA-Tailor (D-Tailor) is a fully extendable software framework for biological sequence analysis and multi-objective sequence design. D-Tailor permits the seamless integration of an arbitrary number of sequence analysis tools into a Monte-Carlo algorithm that evolves synthetic sequences towards user-defined goals. -
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CABBaGe
Classification Algorithm Based on a Bayesian method for Genomics
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faif
C++ header only library with AI and bioinformatics algorithms
C++ header only library, small and fast; Naive Bayesian Classifier, Decision Tree Classifier (ID3), DNA/RNA nucleotide second structure predictor, timeseries management, timeseries prediction, generic Evolutionary Algorithm, generic Hill Climbing algorithm and others. -
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GenCodeGenerator
C++ class to generate biologically plausible genetic codes
...By default, the class "GeneticCode" generates alternative genetic codes, with the reqirement of block structure, and, optionally, with the assumption of stereochemical or biosynthetic models (to impose the assumption of the adaptive model, simply filter the codes using the error_cost() function). See Appendix in Makukov & shCherbak (2017) for the description of the algorithm. The code requires Qt 5. To compile the provided example, run 'qmake' to produce the Makefile, and then run 'make' to compile the executable file. License: Public Domain. -
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SUPERmerge
ChIP-seq coverage island analysis algorithm for broad histone marks
SUPERmerge is a ChIP-seq read pileup analysis and annotation algorithm for investigating alignment (BAM) files of diffuse histone modification ChIP-seq datasets with broad chromatin domains at a single base pair resolution level. SUPERmerge allows flexible regulation of a variety of read pileup parameters, thereby revealing how read islands aggregate into areas of coverage across the genome and what annotation features they map to within individual biological replicates. -
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INTEGRATE: Calling gene fusions with exact fusion junctions and genomic breakpoints by combining RNA-Seq and WGS data. To download source code, reference manual and test case, please go to 'Files'. Also refer to 'Wiki' for details.
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MUMAL2
Multivariate analysis of MS/MS data using ML techniques
Program described in the paper: MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm, 2016. By Fabio R. Cerqueira; Adilson M. Ricardo; Alcione P. Oliveira; Armin Graber; Christian Baumgartner. -
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erne
ERNE - Extended Randomized Numerical alignEr
We present ERNE (Extended Randomized Numerical alignEr), a short string alignment package whose goal is to provide an all-inclusive set of tools to handle short (NGS-like) reads. ERNE comprises ERNE-FILTER (read trimming and continamination filtering), ERNE-MAP (core alignment tool/algorithm), ERNE-BS5 (bisulfite treated reads aligner), and ERNE-PMAP/ERNE-PBS5 (distributed versions of the aligners), -
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iCAS - An Illumina Clone Assembly System
An Illumina clone assembly system using SOAPdenovo and ABySS
...However, assemblies obtained using current whole genome assemblers are often fragmented and sometimes have issues of genome completeness owing to different data characteristics introduced by multiplexed sequencing. With iCAS the data filtering process is based on a novel kmer frequency algorithm, resulting in near perfect pre-assembly reads. Contigs are generated using different assembly algorithms and then merged together to achieve longer continuity. Re-aligning all the reads back to the draft contigs and recalibrating each sequence base achieves a final consensus. Using finished clones for QC, the pipeline is able to obtain assemblies with clone coverage of 99.7% and consensus base quality of Q39. ... -
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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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GeneticAlgorithms
Framework for using the Genetic Algorithms optimization heuristic.
GeneticAlgorithms is a simple and lightweight framework to implement an optimization heuristic following the Genetic Algorithms model. A genetic algorithm mimics the natural processes of evolution, selection and "survival of the fittest". This framework is intuitive and good integrated with Java 1.5 SDK and later. -
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NOFI ranking
The Non-Outlier Fragment Ion ranking for enhaced DIA quantification
The NOFI ranking algorithm has been developed to assign low priority to fragment ions affected by interference. The implementation is an R script that can be customized. A future version will contain a modular version. The outline is as follows: 1) The input contains the list of SWATH fragment ion XICs from the identified and quantified peptides by software tools such as Skyline and OpenSWATH. 2) The first step in NOFI is the computation of the 4 attributes (RTd, FWHMd, IRd and IRrep) used to represent each fragment ion as a vector. 3) Multivariate outlier detection techniques are used to rank all the fragment ions from each peptide. 4) Several figures are generated (a pdf file) to visualize the effect of the Top-N fragment ions over different indicators. 5) The user can choose the number of top fragment ions per peptide, thereby utilizing the optimal subset of high priority Top-N NOFIs for quantification while excluding the impaired fragment ions. -
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...Some Key features of the tool are.... (1) Configured for 4 open source algorithms to perform database searching for peptide identification. Any combination of the 4 algorithm can be chosen. (2) Lists out the genome search specific peptides(Novel peptides). (3) Spectral matches can be visualized for the quality assessment. (4) Lists out the novel proteins and changes in the existing protein annotations. (5) A Visual genomic context of the novel peptides can also be generated.
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fitGCP
Fitting genome coverage distributions with mixture models
...Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147
