Assessing Deviations from "Normality"
Our normative molecular-genetic databank comprises an extensive selection of genotypes
derived from 15,000 ethnically diverse subjects and calibrated according to Zurich standards.
The samples included in the databank have been specifically selected for investigations into the
genetic predisposition to complex disorders, such as schizophrenia, schizoaffective disorders,
bipolar illness, depression, Alzheimer disease, alcohol dependence, hypertension, and asthma.
Integrating Genetic and Physical Information
Currently available genetic and physical maps differ in a variety of basic features, in particular,
with respect to the total length of the chromosomes. Consequently, the question arises as to the
extent to which genetic maps are compatible with each other, as well as to the methods with which
genetic maps can be transformed into one another.
Program Package Master.GEN
The program package Master.GEN encompasses a collection of 48 programs especially designed to meet
the requirements of multivariate analyses of genotypic feature vectors.
As a key feature, Master.GEN supports pattern recognition techniques and adaptive algorithms ("neural
nets") that can also be used to structurally decompose an ethnically diverse sample, if genetic and
environmental factors underlying the same phenotype are expected to vary among ethnically diverse
subgroups.
Neural Network Analysis
Neural Network Analysis (NNA) provides powerful tools for modeling pre-specified responses to complex,
multidimensional input stimuli. It is the specific advantage of NNA that no causal relationship
between stimuli and response is required. Since NNA relies on adaptive learning strategies, experienced
users can easily fit virtually any set of nondegenerate stimuli to any set of responses, provided a
sufficiently large and representative set of learning probes is available.