Search Results for "hard"

...rDock is mainly written in C++ and accessory scripts and programs are written in C++, perl or python languages. The full rDock software package requires less than 50 MB of hard disk space and it is compilable in all Linux computers. Thanks to its design and implementation, it can be installed on a computation cluster and deployed on an unlimited number of CPUs, allowing HTVS campaigns to be carried out in a matter of days. The rDock program was developed from 1998 to 2006 by the software team at RiboTargets (subsequently Vernalis (R&D) Ltd). ...

CUSHAW3 is an open-source parallelized, sensitive and accurate short-read aligner. This aligner proposes a general approach to properly aligning both easy and hard reads to large genomes such as the human genome. Perform evaluation on alignment quality reals that CUSHAW3 consistently outperforms CUSHAW2, BWA-MEM, Bowtie2 and GEM in terms of single-end and paired-end alignment. Furthermore, our aligner has demonstrated better paired-end alignment performance than Novalign3 for short-reads with high error rates.

...InMethyl uses bowtie high-throughoutput aligner to identify potential mis-priming sites in the bisulfite treated or intact genome and then – undesirable potential PCR products. InMethyl provides a balance between various characteristics that allows to pick up primers in hard-to-study genomic regions. This balance is based on the calculation of scoring factor including primer pair specificity, nucleotide composition (sequence complexity), thermodynamic features (melting temperature, dimers dG etc.), presence of CpG-sites and other parameters. Users are intended to customize the desired or limit ranges of these values, as well as penalties for out-of-bounds values. ...

...In experiments with real-life data, the algorithms were shown to be able to construct complete non-redundant sets of patterns for chemical datasets involving several thousands of molecules as well as for comparably large datasets from genomics or proteomics. The included relational learning algorithms are tailored towards so-called tree-like features for which some otherwise very hard sub-problems (NP-hard) become tractable.

This tool is designed to solve generalized pattern matching problem, by which we only find a set of sub-patterns, ignoring the gaps in between the sub-patterns. This tool is extremely fast and also has good tolerance to errors.