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Interpreting Electrocardiograms, Designing CRISPR sgRNAs, and Improving New Analyses of Old MRI Data: the PLOS Comp Biol March issue

bchadwick Computational biology Genetics Genomics Molecular biology Neuroscience PLOS Computational Biology Systems biology

Check out our highlights from the PLOS Computational Biology March issue:

 

Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study

Models and procedure used to develop the algorithm. Image Credit: Alday et al.
Models and procedure used to develop the algorithm. Image Credit: Alday et al.

Atrial tachy-arrhythmias are associated with irregular excitation waves arising from re-entrant excitation, multiple wavelets or rapid focal activity. Identifying the origin of the irregular activity may be vital for diagnosis and treatment of the disorder.  In this study, Henggui Zhang and colleagues use a biophysically detailed model of the human atria and torso to develop an algorithm based on the correlation between the electrocardiogram (ECG) signal from a 64-lead vest and the location of rapid focal and re-entrant excitation.

 

Scalable design of paired CRISPR guide RNAs for genomic deletion

CRISPR-Cas9 technology can be used to engineer precise genomic deletions with pairs of single guide RNAs (sgRNAs). This approach has been widely adopted for diverse applications, from disease modelling of individual loci to parallelized loss-of-function screens of thousands of regulatory elements. However, no solution has been presented for the unique bioinformatic design requirements of CRISPR deletion. Rory Johnson and colleagues present CRISPETa, a pipeline for flexible and scalable paired sgRNA design based on an empirical scoring model.

 

March issue image: the autism awareness ribbon. Image credit: Howsmon et al.
March issue image: the autism awareness ribbon. Image credit: Howsmon et al.

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

Magnetic Resonance Imaging (MRI) is a non-invasive way to measure human brain structure that has been used for over 25 years. There are thousands of MRI studies performed every year, generating a substantial amount of data. At the same time, many new data analysis methods are being developed each year. The potential of using new analysis methods on the variety of existing and newly acquired data is hindered by difficulties in software deployment and lack of support for standardized input data. Krzysztof J. Gorgolewski and colleagues propose to use container technology to make deployment of a wide range of data analysis techniques easy.

 

 

Header Image Credit: Alday et al.

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