Kevin C. Chen

The evolution of gene regulation by transcription factors and microRNAs.

Changes in the patterns of gene expression are widely believed to underlie many of the phenotypic differences within and between species. Although much emphasis has been placed on changes in transcriptional regulation, gene expression is regulated at many levels, all of which must ultimately be studied together to obtain a complete picture of the evolution of gene expression. Here we compare the evolution of transcriptional regulation and post-transcriptional regulation that is mediated by microRNAs, a large class of small, non-coding RNAs in plants and animals, focusing on the evolution of the individual regulators and their binding sites. As an initial step towards integrating these mechanisms into a unified framework, we propose a simple model that describes the transcriptional regulation of new microRNA genes.

Finding Frequent Items in Data Streams

We present a 1-pass algorithm for estimating the most frequent items in a data stream using limited storage space. Our method relies on a data structure called a COUNT SKETCH, which allows us to reliably estimate the frequencies of frequent items in the stream. Our algorithm achieves better space bounds than the previously known best algorithms for this problem for several natural distributions on the item frequencies. In addition, our algorithm leads directly to a 2-pass algorithm for the problem of estimating the items with the largest (absolute) change in frequency between two data streams. To our knowledge, this latter problem has not been previously studied in the literature.

Natural selection on human microRNA binding sites inferred from SNP data.

A fundamental problem in biology is understanding how natural selection has shaped the evolution of gene regulation. Here we use SNP genotype data and techniques from population genetics to study an entire layer of short, cis-regulatory sites in the human genome. MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally repress mRNA through cis-regulatory sites in 3′ UTRs. We show that negative selection in humans is stronger on computationally predicted conserved miRNA binding sites than on other conserved sequence motifs in 3′ UTRs, thus providing independent support for the target prediction model and explicitly demonstrating the contribution of miRNAs to darwinian fitness. Our techniques extend to nonconserved miRNA binding sites, and we estimate that 30%–50% of these are functional when the mRNA and miRNA are endogenously coexpressed. As we show that polymorphisms in predicted miRNA binding sites are likely to be deleterious, they are candidates for causal variants of human disease. We believe that our approach can be extended to studying other classes of cis-regulatory sites.

Bioinformatics for Whole-Genome Shotgun Sequencing of Microbial Communities

The application of whole-genome shotgun sequencing to microbial communities represents a major development in metagenomics, the study of uncultured microbes via the tools of modern genomic analysis. In the past year, whole-genome shotgun sequencing projects of prokaryotic communities from an acid mine biofilm, the Sargasso Sea, Minnesota farm soil, three deep-sea whale falls, and deep-sea sediments have been reported, adding to previously published work on viral communities from marine and fecal samples. The interpretation of this new kind of data poses a wide variety of exciting and difficult bioinformatics problems. The aim of this review is to introduce the bioinformatics community to this emerging field by surveying existing techniques and promising new approaches for several of the most interesting of these computational problems.

Printed Carbon Nanotube Electronics and Sensor Systems

Printing technologies offer large-area, high-throughput production capabilities for electronics and sensors on mechanically flexible substrates that can conformally cover different surfaces. These capabilities enable a wide range of new applications such as low-cost disposable electronics for health monitoring and wearables, extremely large format electronic displays, interactive wallpapers, and sensing arrays. Solution-processed carbon nanotubes have been shown to be a promising candidate for such printing processes, offering stable devices with high performance. Here, recent progress made in printed carbon nanotube electronics is discussed in terms of materials, processing, devices, and applications. Research challenges and opportunities moving forward from processing and system-level integration points of view are also discussed for enabling practical applications.

Diffusion of molecules in brain extracellular space: theory and experiment.

Volume transmission depends on the migration of informational substances through brain extracellular space (ECS) and almost always involves diffusion; basic concepts of diffusion are outlined from both the microscopic viewpoint based on random walks and the macroscopic viewpoint based on the solution of equations embodying Ficks Laws. In a complex medium like the brain, diffusing molecules are constrained by the local volume fraction of the ECS and tortuosity, a measure of the hindrance imposed by cellular obstacles. Molecules can also experience varying degrees of uptake or clearance. Bulk flow and the extracellular matrix may also play a role. Examples of recent work on diffusion of tetramethylammonium (molecular weight, 74) in brain slices, using iontophoretic application and ion-selective microelectrodes, are reviewed. In slices, the volume fraction is about 20% and tortuosity about 1.6, both similar to values found in the intact brain. Using integrative optical imaging, results obtained with dextrans and albumins up to a molecular weight of 70,000 are summarized, for such large molecules the tortuosity is about 2.3. Experiments using synthetic long-chain PHPMA polymers up to 1,000,000 molecular weight show that these molecules also diffuse in the ECS but with a tortuosity of about 1.6. Studies with osmotic challenge show that volume fraction and tortuosity do not vary together as expected when the size of the ECS changes; a model is presented that explains the osmotic-challenge on the basis of changes in cell shape. Finally, new analytical insights are provided into the complex movement of potassium in the brain.

Spatial Buffering of Potassium Ions in Brain Extracellular Space

It has long been assumed that one important mechanism for the dissipation of local potassium gradients in the brain extracellular space is the so-called spatial buffer, generally associated with glial cells. To date, however, there has been no analytical description of the characteristic patterns of K(+) clearance mediated by such a mechanism. This study reanalyzed a mathematical model of Gardner-Medwin (1983, J. Physiol. (Lond.). 335:393-426) that had previously been solved numerically. Under suitable approximations, the transient solutions for the potassium concentrations and the corresponding membrane potentials of glial cells in a finite, parallel domain were derived. The analytic results were substantiated by numerical simulations of a detailed two-compartment model. This simulation explored the dependence of spatial buffer current and extracellular K(+) on the distribution of inward rectifier K(+) channels in the glial endfoot and nonendfoot membranes, the glial geometric length, and the effect of passive KCl uptake. Regarding the glial cells as an equivalent leaky cable, the analyses indicated that a maximum endfoot current occurs when the glial geometric length is equal to the corresponding electrotonic space constant. Consequently, a long glial process is unsuitable for spatial buffering, unless the axial space constant can match the length of the process. Finally, this study discussed whether the spatial buffer mechanism is able to efficiently transport K(+) over distances of more than several glial space constants.

Large-Area Compliant Tactile Sensors Using Printed Carbon Nanotube Active-Matrix Backplanes

A 20 × 20 pixel pressure sensor array based on a printed active-matrix single-wall carbon-nanotube thin-film transistor backplane is presented. Using a gravure printing process that is compatible with fully printed large-area roll-to-roll processing, a 97% device yield is obtained on the 400-transistor backplane. As a proof of concept, pressure sensors are integrated to map the applied tactile pressure across the array.

Perturbation expansion of Alt's cell balance equations reduces to Segel's one-dimensional equations for shallow chemoattractant gradients

The cell balance equations of Alt are rigorously studied and perturbatively expanded into forms similar to Segels one-dimensional phenomenological cell balance equations by considering the simplifying case of bacterial density possessing symmetry in the x and y directions responding to an attractant gradient present only in the z direction. We prove that for shallow attractant gradients the lumped integrals involving the tumbling probability frequency distribution and bacterial density distribution in the

Theory relating in vitro and in vivo microdialysis with one or two probes

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