An information theory model of hydrophobic interactions.

A molecular model of poorly understood hydrophobic effects is heuristically developed using the methods of information theory. Because primitive hydrophobic effects can be tied to the probability of observing a molecular-sized cavity in the solvent, the probability distribution of the number of solvent centers in a cavity volume is modeled on the basis of the two moments available from the density and radial distribution of oxygen atoms in liquid water. The modeled distribution then yields the probability that no solvent centers are found in the cavity volume. This model is shown to account quantitatively for the central hydrophobic phenomena of cavity formation and association of inert gas solutes. The connection of information theory to statistical thermodynamics provides a basis for clarification of hydrophobic effects. The simplicity and flexibility of the approach suggest that it should permit applications to conformational equilibria of nonpolar solutes and hydrophobic residues in biopolymers.

Blind separation of auditory event-related brain responses into independent components

Averaged event-related potential (ERP) data recorded from the human scalp reveal electroencephalographic (EEG) activity that is reliably time-locked and phase-locked to experimental events. We report here the application of a method based on information theory that decomposes one or more ERPs recorded at multiple scalp sensors into a sum of components with fixed scalp distributions and sparsely activated, maximally independent time courses. Independent component analysis (ICA) decomposes ERP data into a number of components equal to the number of sensors. The derived components have distinct but not necessarily orthogonal scalp projections. Unlike dipole-fitting methods, the algorithm does not model the locations of their generators in the head. Unlike methods that remove second-order correlations, such as principal component analysis (PCA), ICA also minimizes higher-order dependencies. Applied to detected—and undetected—target ERPs from an auditory vigilance experiment, the algorithm derived ten components that decomposed each of the major response peaks into one or more ICA components with relatively simple scalp distributions. Three of these components were active only when the subject detected the targets, three other components only when the target went undetected, and one in both cases. Three additional components accounted for the steady-state brain response to a 39-Hz background click train. Major features of the decomposition proved robust across sessions and changes in sensor number and placement. This method of ERP analysis can be used to compare responses from multiple stimuli, task conditions, and subject states.

Noise in neurons is message dependent

Neuronal responses are conspicuously variable. We focus on one particular aspect of that variability: the precision of action potential timing. We show that for common models of noisy spike generation, elementary considerations imply that such variability is a function of the input, and can be made arbitrarily large or small by a suitable choice of inputs. Our considerations are expected to extend to virtually any mechanism of spike generation, and we illustrate them with data from the visual pathway. Thus, a simplification usually made in the application of information theory to neural processing is violated: noise is not independent of the message. However, we also show the existence of error-correcting topologies, which can achieve better timing reliability than their components.

A general procedure for locating and analyzing protein-binding sequence motifs in nucleic acids

In the last decade, two tools, one drawn from information theory and the other from artificial neural networks, have proven particularly useful in many different areas of sequence analysis. The work presented herein indicates that these two approaches can be joined in a general fashion to produce a very powerful search engine that is capable of locating members of a given nucleic acid sequence family in either local or global sequence searches. This program can, in turn, be queried for its definition of the motif under investigation, ranking each base in context for its contribution to membership in the motif family. In principle, the method used can be applied to any binding motif, including both DNA and RNA sequence families, given sufficient family size.

The human XPG gene: gene architecture, alternative splicing and single nucleotide polymorphisms

Defects in the XPG DNA repair endonuclease gene can result in the cancer-prone disorders xeroderma pigmentosum (XP) or the XP–Cockayne syndrome complex. While the XPG cDNA sequence was known, determination of the genomic sequence was required to understand its different functions. In cells from normal donors, we found that the genomic sequence of the human XPG gene spans 30 kb, contains 15 exons that range from 61 to 1074 bp and 14 introns that range from 250 to 5763 bp. Analysis of the splice donor and acceptor sites using an information theory-based approach revealed three splice sites with low information content, which are components of the minor (U12) spliceosome. We identified six alternatively spliced XPG mRNA isoforms in cells from normal donors and from XPG patients: partial deletion of exon 8, partial retention of intron 8, two with alternative exons (in introns 1 and 6) and two that retained complete introns (introns 3 and 9). The amount of alternatively spliced XPG mRNA isoforms varied in different tissues. Most alternative splice donor and acceptor sites had a relatively high information content, but one has the U12 spliceosome sequence. A single nucleotide polymorphism has allele frequencies of 0.74 for 3507G and 0.26 for 3507C in 91 donors. The human XPG gene contains multiple splice sites with low information content in association with multiple alternatively spliced isoforms of XPG mRNA.