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Motivation: Capillary electrophoresis (CE) of nucleic acids is a workhorse technology underlying high-throughput genome analysis and large-scale chemical mapping for nucleic acid structural inference. Despite the wide availability of CE-based instruments, there remain challenges in leveraging their full power for quantitative analysis of RNA and DNA structure, thermodynamics and kinetics. In particular, the slow rate and poor automation of available analysis tools have bottlenecked a new generation of studies involving hundreds of CE profiles per experiment.Results: We propose a computational method called high-throughput robust analysis for capillary electrophoresis (HiTRACE) to automate the key tasks in large-scale nucleic acid CE analysis, including the profile alignment that has heretofore been a rate-limiting step in the highest throughput experiments. We illustrate the application of HiTRACE on 13 datasets representing 4 different RNAs, 3 chemical modification strategies and up to 480 single mutant variants; the largest datasets each include 87 360 bands. By applying a series of robust dynamic programming algorithms, HiTRACE outperforms prior tools in terms of alignment and fitting quality, as assessed by measures including the correlation between quantified band intensities between replicate datasets. Furthermore, while the smallest of these datasets required 7–10 h of manual intervention using prior approaches, HiTRACE quantitation of even the largest datasets herein was achieved in 3–12 min. The HiTRACE method, therefore, resolves a critical barrier to the efficient and accurate analysis of nucleic acid structure in experiments involving tens of thousands of electrophoretic bands.Availability: HiTRACE is freely available for download at http://hitrace.stanford.edu.Contact: sryoon@korea.ac.kr; rhiju@stanford.eduSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

We present new Ryle Telescope (RT) observations of the Sunyaev-Zel'dovich (SZ) decrement from the cluster Abell 773. The field contains a number of faint radio sources that required careful subtraction. We use ASCA observations to measure the gas temperature and a ROSAT HRI image to model the gas density distribution. Normalizing the gas distribution to fit the RT visibilities returns a value of H[sub 0] of 77[sup +19, sub -15] km s[sup -1] Mpc[sup -1] (1σ errors) for an Einstein-de Sitter universe, or 85[sup +20, sub -17] km[sup -1] Mpc[sup -1] for a flat model with Ω[sub Λ] = 0.7. The errors quoted include estimates of the effects of the principal errors: noise in the SZ measurement, gas temperature uncertainty and line-of-sight depth uncertainty. [ABSTRACT FROM AUTHOR]

Describes a maximum-likelihood approach to removing radio sources from observations of the Sunyaev-Zel'dovich effect. Removal of contaminating radio sources; Cosmology; Galaxies.

We present the results of radio, optical and near-infrared observations of the field of TOC J0233.3+3021, a cluster of milliJansky radio sources from the TexOx Cluster survey. In an observation of this field with the Ryle Telescope (RT) at 15 GHz, we measure a decrement in the cosmic microwave background (CMB) of -675±95 μJy on the RT's≈0.65 kλ baseline. Using optical and infrared imaging with the McDonald 2.7-m Smith Reflector, the Calar Alto 3.5-m telescope and the United Kingdom Infrared Telescope (UKIRT), we identify the host galaxies of five of the radio sources and measure magnitudes of R≈24 , J≈20 , K≈18 . The cosmic microwave background (CMB) decrement is consistent with the Sunyaev–Zel'dovich (SZ) effect of a massive cluster of galaxies, which if modelled as a spherical King profile of core radius θ[sub C]=20 arcsec has a central temperature decrement of 900 μK. The magnitudes and colours of the galaxies are consistent with those of old ellipticals at z∼1 . We therefore conclude that TOC J0233.3+3021 is a massive, high redshift cluster. These observations add to the growing evidence for a significant population of massive clusters at high redshift, and demonstrate the effectiveness of combining searches for active galactic nuclei (AGN) ‘signposts’ to clusters with the redshift-independence of the SZ effect. [ABSTRACT FROM AUTHOR]

Summary: We have established an RNA mapping database (RMDB) to enable structural, thermodynamic and kinetic comparisons across single-nucleotide-resolution RNA structure mapping experiments. The volume of structure mapping data has greatly increased since the development of high-throughput sequencing techniques, accelerated software pipelines and large-scale mutagenesis. For scientists wishing to infer relationships between RNA sequence/structure and these mapping data, there is a need for a database that is curated, tagged with error estimates and interfaced with tools for sharing, visualization, search and meta-analysis. Through its on-line front-end, the RMDB allows users to explore single-nucleotide-resolution mapping data in heat-map, bar-graph and colored secondary structure graphics; to leverage these data to generate secondary structure hypotheses; and to download the data in standardized and computer-friendly files, including the RDAT and community-consensus SNRNASM formats. At the time of writing, the database houses 53 entries, describing more than 2848 experiments of 1098 RNA constructs in several solution conditions and is growing rapidly.Availability: Freely available on the web at http://rmdb.stanford.eduContact: rhiju@stanford.eduSupplementary information: Supplementary data are available at Bioinformatics Online. [ABSTRACT FROM AUTHOR]

Rapid RNA synthesis of comprehensive single mutant libraries and targeted multiple mutant libraries is enabling new multidimensional chemical approaches to solve RNA structures. PCR assembly of DNA templates and in vitro transcription allow synthesis and purification of hundreds of RNA mutants in a cost-effective manner, with sharing of primers across constructs allowing significant reductions in expense. However, these protocols require organization of primer locations across numerous 96 well plates and guidance for pipetting, non-trivial tasks for which informatics and visualization tools can prevent costly errors. We report here an online tool to accelerate synthesis of large libraries of desired mutants through design and efficient organization of primers. The underlying program and graphical interface have been experimentally tested in our laboratory for RNA domains with lengths up to 300 nucleotides and libraries encompassing up to 960 variants. In addition to the freely available Primerize-2D server, the primer design code is available as a stand-alone Python package for broader applications. [ABSTRACT FROM AUTHOR]