Tutorial movies BioNumerics Seven

Watch our online training videos to learn more about the BioNumerics version 7.x software. For GelCompar II or previous BioNumerics releases, check out our version 6.x tutorial videos. If you don't find what you are looking for, please let us know!

Training video categories:

DatabaseBack to top

All information pertaining the BIONUMERICS database. This includes import of descriptive information about strains, accession or biological samples (commonly referred to as entries in BIONUMERICS), modifications to the database layout and setup, entry selections, user management, etc.

FingerprintsBack to top

Any type of data that can be translated into a densitometric curve is considered a fingerprint type in the BIONUMERICS and GelCompar II software. This includes commonly used genotyping methods employing agarose or polyacrylamide slab gel electrophoresis (PFGE, rep-PCR, RAPD, PCR-DGGE, etc.), in which case the data are usually imported as two-dimensional gel images (bitmaps). Another major group consists of capillary electrophoresis profiles such as AFLP, ARISA, T-RFLP, etc. Here, the raw electropherograms generated by an automated sequencer (genetic analyzer) or derived peak table text files can be imported. Finally, any other profile (generated e.g. by gas chromatography, HPLC or spectrophotometry) that can be seen as peaks or bands, can be analyzed as a fingerprint.

SpectraBack to top

Spectrum types (or spectra) share some features with fingerprints, but are specifically designed to hold and process e.g. mass spectrometry data such as MALDI TOF MS, LC MS, ESI and SELDI.

CharactersBack to top

A character is basically a name-value pair of which the value can be binary, multi-state or continuous. Because of this very broad definition, a wide variety of data can be analyzed as character types (= an array of characters). This includes morphological and biochemical features, commercial test panels (API®, Biolog®, Vitek®, etc.), antibiotics resistance profiles, fatty acid profiles, microarrays, SNP arrays, repeat numbers in MLVA, allelic profiles in MLST, etc.