This paper presents the application of special unsupervised neural networks (self-organizing maps) to different domains, as sleep apnea discovery, protein sequences analysis and tumor classification. An enhancement of the original algorithm, as well as the introduction of several hierachical...

Research concerning the quantitative trait loci (QTL) mapping in plant genetics usually consists of two stages. The first stage is concerned with collecting data while the second one, based on the data collected, is concerned with a proper QTL study. The final inferences are strictly connected...

The determination of toxicokinetic parameters is an essential component in the risk assessment of potential harmful chemicals. It’s a first step to analyse the processes which are involved in the development of DNA adducts and might therefore lead to the development of cancer. The complete...

The structural analysis of proteins is fundamental to the analysis of protein functions. In this context, sequence-structure alignment methods are important among the different empirical methods. In order to assess the quality of sequence-structure alignments, a statistical method using a...

The secondary structure classification of amino acid sequences can be carried out by a statistical analysis of sequence and structure data using state-space models. Aiming at this classification, a modified filter algorithm programmed in S is applied to data of three proteins. The application...

Two different estimation techniques for the spectrum of a nonstationary time series are compared empirically. Both of them are assuming a time-dependent autoregressive (AR-) model for the data. The first estimation technique used is the Frequency State Dependent Model (FSDM-) technique (Schmitz...

The expanding availability of protein data enforces the application of empirical methods necessary to recognize protein structures. In this paper a sequence-structure alignment method is described and applied to various Ubiquitin-like folded Ras-binding domains. On the basis of two probability...

In this paper, hidden Markov models (HMMs) are discussed in the context of molecular biological sequence analysis. The statistics relevant in the HMM approach are described in detail. An HMM based method is used to analyze two proteins that contain short protein repeats (SPRs). As a benchmark, a...