We are proud to announce the release of version 7.0 of our flagship software suite BioNumerics. The BioNumerics software provides a universal platform for databasing and analysis of 1D patterns, genotype/phenotype arrays, and DNA/protein sequences. The software provides powerful databasing, integrated networking and a wide range of data mining, clustering, identification, and statistical applications. BioNumerics is designed for lab-wide databasing and analysis of biological data in laboratories of any size and is in use in thousands of public and private research sites worldwide. The software is referenced in thousands of peer-reviewed scientific papers. In addition, BioNumerics and its server application BioNumerics Server are the cornerstones for numerous national and international research projects and epidemiological surveillance networks. 
comes with several fundamental improvements and a plethora of new analysis possibilities with a strong focus on user friendliness.
Among the most important new features are an all-new experiment type for analyzing spectrum data, which provides a comprehensive platform for importing, preprocessing and summarizing spectrum fingerprints obtained by e.g. MALDI-TOF, SELDI and ESI.
Users of techniques such as MLVA, MLPA, AFLP and SSR will appreciate the much improved processing workflow for capillary sequencer data, which allows the raw electropherograms of a complete genetic analyzer run to be processed in seconds rather than in minutes.
The new sequence read sets experiment type renders into a powerful next-generation sequence data management platform, by offering an integrated environment for importing, preprocessing and analyzing sets of reads from high-throughput sequencers (e.g. Roche/454, Illumina, IonTorrent) or from public repositories. Sequence read sets also form the starting point of the comprehensive metagenomics tools for the characterization of microbial communities using deep sequencing of a phylogenetic marker (e.g. 16S rRNA).
features a completely new module for the alignment and clustering of whole genome maps obtained from the Argus™ Whole Genome Mapping System (OpGen), mainly focused on strain typing and characterization.
The identification framework in has been completely revised, resulting in more user-friendly identification projects and in the addition of new state-of-the-art classifier algorithms such as Support Vector Machines and Naive Bayesian Classifiers. The framework contains extensive cross-validation and parameter optimization tools.
In addition to these new applications, BioNumerics version 7.0 contains a large number of new interface and database enhancements. This includes the generalized use of object views and attachments, an improved import wizard, a convenient search tool to rapidly retrieve database information, the new database design with levels and dependencies to deal with replicate measurements, an online help that is accessible from every dialog box and window, and much more.