BioNumerics Seven tutorials

Click on a tutorial title to go to a page with the tutorial description and links to download a PDF file containing step-by-step instructions and sample data (if applicable). All tutorials are based on the latest software version.

Tutorial 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.

Sequence read setsBack to top

A sequence read set is designed to hold large sets of short reads generated by next generation sequencing (NGS). Base sequences and their associated quality scores are stored for single-end and paired-end reads, originating from various high-throughput pyrosequencing platforms such as Roche 454, Illumina Solexa, Ion Torrent, etc.

Trend dataBack to top

Trend data refers to sequential measurements that express an evolution of one parameter in function of another. Examples include enzymatic activity, growth curves, (high resolution) melting curves, etc. Such data can be imported, analyzed and compared (by means of parameters calculated on regression curves) in the BioNumerics software.

Whole genome mapsBack to top

Whole genome maps are high resolution, ordered whole genome restriction maps from single microbial DNA molecules obtained from the Argus™ Whole Genome Mapping System (OpGen).

MLVA analysisBack to top

Multi-Locus VNTR (Variable Number of Tandem Repeats) Analysis using the BioNumerics MLVA plugin. See the MLVA application page for a complete overview.

wgSNP analysisBack to top

Whole-genome Single Nucleotide Polymorphism (SNP) analysis using BioNumerics. See the wgSNP application page for a complete overview.

spa-typingBack to top

Typing of Staphylococcus aureus strains using repeat sequences in the spa-gene. See the spa typing application page for a complete overview.

Connected databasesBack to top

BioNumerics stores its data in a relational (SQL) database, usually referred to as “connected database” in the software. Following database types are supported: Microsoft SQL Server, Microsoft Access, Oracle and MySQL. This topic contains information on the creation and setup of databases in the database management software (DBMS) and on how to link BioNumerics via an ODBC connection to an existing database.