Search Results for "no knowledge"

FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data (paired-end reads from Illumina NGS platforms like Solexa and HiSeq) from diseased samples. The aims of FusionCatcher are: - very good detection rate for finding candidate fusion genes, - very easy to use (i.e. no a priori knowledge of databases and bioinformatics is needed in order to run FusionCatcher), - very good detection of challenging fusion genes, like for example IGH fusions, CIC fusions, DUX4 fusions, CRLF2 fusions, TCF3 fusions, etc. - to be as automatic as possible (i.e. the FusionCatcher will choose automatically the best parameters in order to find candidate fusion genes, e.g. finding automatically the adapters, building the exon-exon junctions automatically based on the length of the input reads, etc.) while providing the best possible detection rate for finding fusion genes.

The Collaborative Computational Project for NMR (CCPN) provides tools and knowledge to maximise the impact of the biological NMR studies. The CCPN software facilitates data analysis and software integration. The project actively promotes the exchange of knowledge and provides training and best practices for the NMR community. CCPN also has a leading role in the development of a NMR data-sharing standard and coordination of NMR instrumentation proposals for RCUK and BIS. ...

...We optimized the P3BSseq parameters for both directional and non-directional libraries, and for both single-end and paired-end reads of Whole Genome and Reduced Representation BSseq. P3BSseq is a user-friendly streamlined solution for BSseq upstream analysis, requiring only basic computer and NGS knowledge.

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. ...

The SeqSelector toolset is a suite of user-friendly, platform independent python scripts to facilitate selection of sequences for targeted enrichment of next-generation libraries through hybridization-based sequence capture. The scripts require no knowledge of programming, and can be applied to genome sequences of model or non-model species. We suggest a workflow in which genes of interest are first identified from previous studies and publicly available datasets of functional gene annotation. Once a list of candidate genes has been identified, their sequences are selected from the reference genome. ...

...BiSA can also annotate binding regions of interest with nearby genes. The results of overlap analysis can be imported into the Knowledge Base, allowing them to go into downstream analysis and independent annotation. A Venn diagram tool is also integrated into the software to allow users to visualize overlap results.

...If you use this code please cite this paper: P. Davis-Desmond and Diego Mollá. Detection of Evidence in Clinical Research Papers (2012). Australasian Workshop On Health Informatics and Knowledge Management (HIKM 2012), Melbourne, Australia. http://www.ics.mq.edu.au/~diego/publications/hikm12.pdf

This project seeks to integrate knowledge, methods and data from various disciplines through the design and implementation of a system that allows for communications between languages and different platforms.