Biomedical subjects

R Sacile

Publications and source records attributed to R Sacile.

6 recordsLinked to original sources

PubMed1996

An object programming based environment for protein secondary structure prediction.

The most frequently used methods for protein secondary structure prediction are empirical statistical methods and rule based methods. A consensus system based on object-oriented programming is presented, which integrates the two approaches with the aim of improving the prediction quality. This system uses an object-oriented knowledge representation based on the concepts of conformation, residue and protein, where the conformation class is the basis, the residue class derives from it and the protein class derives from the residue class. The system has been tested with satisfactory results on several proteins of the Brookhaven Protein Data Bank. Its results have been compared with the results of the most widely used prediction methods, and they show a higher prediction capability and greater stability. Moreover, the system itself provides an index of the reliability of its current prediction. This system can also be regarded as a basis structure for programs of this kind.

Amino Acid Sequence↗

PubMed1994

Secondary structure of noxiustoxin and charybdotoxin from hydropathy power spectra.

The analysis of the hydropathy profile power spectra provides a basis for studies of pattern matching between the primary and secondary structure of peptides. The structural motif obtained with Noxiustoxin (NTX), the first K+ channel blocking peptide described, is composed of a N-terminal beta-strand, a central alpha-helix and a final beta-strand zone, probably forming a beta-sheet. These results were compared with those of Charybdotoxin (ChTX), a potent inhibitor of the high conductance Ca(2+)-activated K+ channel, which presents about 48% similarity with NTX in the amino acid sequence. Our prediction for ChTX secondary structure, which is known by 2D-NMR spectroscopy, yielded a Chou-Fasman quality index Q = 90%. The comparison between the two toxins has guided the interpretation of the data obtained.

Amino Acid Sequence↗

PubMed1993

Peptides secondary structure prediction with neural networks: a criterion for building appropriate learning sets.

Artificial neural networks have been recently applied with success for protein secondary structure prediction. So far, one of the two main aspects on which neural net performance depends, the topology of the net, has been considered. The present work addresses the other main aspect, the building up of the learning set. We present a criterion to build up suitable learning sets based on the alpha-helix percentage. Starting from a set of several well known proteins, we formed 7 groups of proteins with similar helix percentages and we used them for the learning of the same neural net. We found that the best secondary structure prediction for each of the tested proteins (not belonging to the initial set) was the one obtained using the learning set whose helix percentage was closest to that of the tested protein. The accuracy of correct prediction of our method on three types of secondary structure (alpha-helix, beta-sheet and coil), has been compared with the accuracy of other secondary structure prediction methods.

Algorithms↗

PubMedDate not supplied

Sustaining Oncology Studies--SOS: information and support for training, research and exploitation in cancer and related biomedical disciplines.

This paper outlines the development of the Sustaining Oncology Studies Information Resources (SOS Europe), a multimedia World Wide Web (WWW) prototype providing support to experimental and clinical cancer researchers, general practitioners, industry personnel, and university students in the field of oncology in Europe and Italy. The system utilizes applications developed for the WWW and is designed in the most easily understandable approaches possible. The prototype now structures oncology-related information available on the Internet and also places resources maintained locally at users' disposal. The system utilizes a WWW browser as a design platform and HTML to build its Home and subpages and to create hyperlinks to internal and external resources.

Computer Communication Networks↗

PubMedDate not supplied

Using CommonKADS to create a conceptual model of a guideline system for breast cancer prognosis.

One of the major aspects in breast cancer research is the identification of prognostic factors accurate enough to define different therapeutic decisions; each prognostic factor on its own is insufficient for the prediction of the biological behaviour of the tumour, but a combination of these parameters is necessary. The work described here focuses on the definition of a conceptual knowledge model of the prognosis of breast cancer. Our approach to the conceptualization of the problem follows the CommonKADS (Knowledge Acquisition and Design Structuring) Library for Expertise Modelling. The aim of this work is to provide a first conceptualization of breast cancer prognosis while evaluating the efficacy of the CommonKADS methodology in facing the problem.

Artificial Intelligence↗

PubMedDate not supplied

The EPIC project in Savona: an example of dissemination of an EU-AIM project at municipal level.

We present a local Dissemination of EPIC, a project which has been devised to support health and social primary care by an information system. One key point of the EPIC project was a standardization effort at European level, providing a standardized basis for the management system based on client needs for planning and manpower control. Whilst EPIC has been designed as a general community information system, the main EPIC applications focus is on the care of the elderly. Savona is a middle size Italian town with a high percentage of elderly people and has already had an experience of integration of health and social care within an Italian project. It has therefore been regarded as a suitable site for the dissemination of EPIC. The EPIC application solved some of the information problems which emerged during the validation of the previous Italian project, such as the definition of the requirements; the collection, processing and retrieval of the clinical/social data; the definition of responsibilities and relations of the operators.

Aged↗