ABSTRACT
The paper introduces the pre-Hilbert space of standard gene expression (SSGE) based on the normal variability in gene profiles, as revealed by the "spotting" microarray technique. In this space, every point represents a possible gene profile and every continuous curve a possible genetic evolution. The gene "patholog" is defined as the Euclidean distance separating the representative point of the gene profile from the unit, 0-centered hyperball. It is the most general quantification of the alteration in digital genes expression, suitable to define, evaluate, and classify the genetic diseases. Our mathematical model and the afferent computer package allow the researcher to identify the patterns of various genetic afflictions in the SSGE. A publicly available database will be opened where every interested experimentalist could introduce his/her results and process them according to our procedure.
Subject(s)
Gene Expression Profiling , Genetic Diseases, Inborn/classification , Genetic Diseases, Inborn/genetics , Models, Genetic , Gene Expression , Genetic Diseases, Inborn/epidemiology , Humans , Multigene Family , Risk Factors , Severity of Illness IndexABSTRACT
The "spotting" microarray technique, consisting in large sets of DNA sequences spotted on poly-L-lysine-coated glass microscope slides, has been developed to comparatively analyze genome-wide patterns of mRNA expression. It is now a valuable tool employed in order to quantitatively monitor gene expression profiles, as well as to analyze the alterations produced in case of genetic diseases, or induced by different treatments, abnormal nutrition and toxin. Our group improved the standard protocol as well as the results spreadsheet, adding new experiments and mathematical processing procedures in order to increase the accuracy of the data and get new information. In this contribution, we propose and verify two procedures to correct the spot ratios and a new protocol to get the normal variability of the digital gene expression.
Subject(s)
Oligonucleotide Array Sequence Analysis/methods , Oligonucleotide Array Sequence Analysis/standards , Software , Algorithms , Humans , Reproducibility of ResultsABSTRACT
The concept of the ionic channel, as a protein with more discrete ionic conductance levels, is analyzed and a computer program, aiming to simulate its dynamics under the action of a pharmacological agent, is presented. The binding of a pharmacological agent modifies the set of the possible configurations and the channel energy spectrum. Therefore it modifies the transition probabilities and the dwelling times in the excited (generally conductive) states. The program creates a library of simulations of the electric activity of some user designated hypothetical models. The simulations are then statistically compared to the recorded single channel events to select the most suitable model.
Subject(s)
Cell Membrane/chemistry , Computer Simulation , Ion Channel Gating/physiology , Ion Channels/drug effects , Models, Chemical , Cell Membrane/metabolism , Electric Conductivity , Ion Channel Gating/drug effects , Ion Channels/physiology , Membrane Potentials/physiologyABSTRACT
The pre-Hilbert space of normal and pathological states of a living organism is built and a set of functions of medical interest are defined on it. Thus we put in mathematical terms the pathological of a state, the drug, the treatment, the length and the therapeutical effect of a treatment and the therapeutical efficiency of a drug.
Subject(s)
Computer Simulation , Models, Biological , Physiology , Disease , Drug Evaluation , Drug Therapy , Humans , MathematicsABSTRACT
An easy to use, for a physiologist, BASIC program based on a previous published theory (Iacobas & Iacobas 1985, 1987) is presented. The user should introduce the mean values, the allowed fluctuations and the experimentally determined values (at certain time moments) of the parameters which are satisfactorily describing the living system. The computer will then determine the corresponding values of the dimensionless parameters, will compute the pathological for every experimentally studied state and will build the pre-Hilbert space of normal and pathological states of the system. On request, the computer could present on the display the graph for each parameter (natural or dimensionless) and could fit the experimental data with some analytical functions giving their coefficients and the fitting standard errors. The computer could also make predictions (on request) concerning the evolution of the system in any realistic time interval.
