152 research outputs found
HiTRACE-Web: an online tool for robust analysis of high-throughput capillary electrophoresis
To facilitate the analysis of large-scale high-throughput capillary
electrophoresis data, we previously proposed a suite of efficient analysis
software named HiTRACE (High Throughput Robust Analysis of Capillary
Electrophoresis). HiTRACE has been used extensively for quantitating data from
RNA and DNA structure mapping experiments, including mutate-and-map contact
inference, chromatin footprinting, the EteRNA RNA design project and other
high-throughput applications. However, HiTRACE is based on a suite of
command-line MATLAB scripts that requires nontrivial efforts to learn, use, and
extend. Here we present HiTRACE-Web, an online version of HiTRACE that includes
standard features previously available in the command-line version as well as
additional features such as automated band annotation and flexible adjustment
of annotations, all via a user-friendly environment. By making use of
parallelization, the on-line workflow is also faster than software
implementations available to most users on their local computers. Free access:
http://hitrace.or
Prospects for de novo phasing with de novo protein models
In a first systematic exploration of phasing with Rosetta de novo models, it is shown that all-atom refinement of coarse-grained models significantly improves both the model quality and performance in molecular replacement with the Phaser software
Atomic accuracy in predicting and designing non-canonical RNA structure
We present a Rosetta full-atom framework for predicting and designing the non-canonical motifs that define RNA tertiary structure, called FARFAR (Fragment Assembly of RNA with Full Atom Refinement). For a test set of thirty-two 6-to-20-nucleotide motifs, the method recapitulated 50% of the experimental structures at near-atomic accuracy. Additionally, design calculations recovered the native sequence at the majority of RNA residues engaged in non-canonical interactions, and mutations predicted to stabilize a signal recognition particle domain were experimentally validated
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