arXiv subjects

HC Lee

Publications and source records attributed to HC Lee.

5 recordsLinked to original sources

arXiv2009

Integrity of H1 helix in prion protein revealed by molecular dynamic simulations to be especially vulnerable to changes in the relative orientation of H1 and its S1 flank

In the template-assistance model, normal prion protein (PrPC), the pathogenic cause of prion diseases such as Creutzfeldt-Jakob (CJD) in human, Bovine Spongiform Encephalopathy (BSE) in cow, and scrapie in sheep, converts to infectious prion (PrPSc) through an autocatalytic process triggered by a transient interaction between PrPC and PrPSc. Conventional studies suggest the S1-H1-S2 region in PrPC to be the template of S1-S2 $β$-sheet in PrPSc, and the conformational conversion of PrPC into PrPSc may involve an unfolding of H1 in PrPC and its refolding into the $β$-sheet in PrPSc. Here we conduct a series of simulation experiments to test the idea of transient interaction of the template-assistance model. We find that the integrity of H1 in PrPC is vulnerable to a transient interaction that alters the native dihedral angles at residue Asn$^{143}$, which connects the S1 flank to H1, but not to interactions that alter the internal structure of the S1 flank, nor to those that alter the relative orientation between H1 and the S2 flank.

q-bio.BM↗

arXiv2007

Filter Out High Frequency Noise in EEG Data Using The Method of Maximum Entropy

We propose a maximum entropy (ME) based approach to smooth noise not only in data but also to noise amplified by second order derivative calculation of the data especially for electroencephalography (EEG) studies. The approach includes two steps, applying method of ME to generate a family of filters and minimizing noise variance after applying these filters on data selects the preferred one within the family. We examine performance of the ME filter through frequency and noise variance analysis and compare it with other well known filters developed in the EEG studies. The results show the ME filters to outperform others. Although we only demonstrate a filter design especially for second order derivative of EEG data, these studies still shed an informatic approach of systematically designing a filter for specific purposes.

q-bio.QM↗

arXiv2007

Genomes: at the edge of chaos with maximum information capacity

We propose an order index, phi, which quantifies the notion of ``life at the edge of chaos'' when applied to genome sequences. It maps genomes to a number from 0 (random and of infinite length) to 1 (fully ordered) and applies regardless of sequence length. The 786 complete genomic sequences in GenBank were found to have phi values in a very narrow range, 0.037+/-0.027. We show this implies that genomes are halfway towards being completely random, namely, at the edge of chaos. We argue that this narrow range represents the neighborhood of a fixed-point in the space of sequences, and genomes are driven there by the dynamics of a robust, predominantly neutral evolution process.

q-bio.GN↗

arXiv2005

Identifying Biomagnetic Sources in the Brain by the Maximum Entropy Approach

Magnetoencephalographic (MEG) measurements record magnetic fields generated from neurons while information is being processed in the brain. The inverse problem of identifying sources of biomagnetic fields and deducing their intensities from MEG measurements is ill-posed when the number of field detectors is far less than the number of sources. This problem is less severe if there is already a reasonable prior knowledge in the form of a distribution in the intensity of source activation. In this case the problem of identifying and deducing source intensities may be transformed to one of using the MEG data to update a prior distribution to a posterior distribution. Here we report on some work done using the maximum entropy method (ME) as an updating tool. Specifically, we propose an implementation of the ME method in cases when the prior contain almost no knowledge of source activation. Two examples are studied, in which part of motor cortex is activated with uniform and varying intensities, respectively.

q-bio.NC↗

arXiv2003

Evidence for growth of microbial genomes by short segmental duplications

We show that textual analysis of microbial genomes reveal telling footprints of the early evolution of the genomes. The frequencies of word occurrence of random DNA sequences considered as texts in their four nucleotides are expected to obey Poisson distributions. It is noticed that for words less than nine letters the average width of the distributions for complete microbial genomes is many times that of a Poisson distribution. We interpret this phenomenon as follows: the genome is a large system that possesses the statistical characteristics of a much smaller ``random'' system, and certain textual statistical properties of genomes we now see are remnants of those of their ancestral genomes, which were much shorter than the genomes are now. This interpretation suggests a simple biologically plausible model for the growth of genomes: the genome first grows randomly to an initial length of approximately one thousand nucleotides (1k nt), or about one thousandth of its final length, thereafter mainly grows by random segmental duplication. We show that using duplicated segments averaging around 25 nt, the model sequences generated possess statistical properties characteristic of present day genomes. Both the initial length and the duplicated segment length support an RNA world at the time duplication began. Random segmental duplication would greatly enhance the ability of a genome to use its hard-to-acquire codes repeatedly, and a genome that practiced it would have evolved enormously faster than those that did not.

physics.bio-ph↗