Behind the Paper
The real stories behind the latest research papers, from conception to publication, the highs and the lows
Improving Structural Variation Detection Accuracy in Repetitive Regions Using Hybrid Algorithms and SFS Signatures
SVDSS combines ideas from traditional mapping-based and assembly-based SV detection algorithms with the novel mapping-free Substring-free Sample-specific Strings (SFS) framework to achieve a 15% recall improvement over state-of-the-art methods in detecting SVs in repetitive regions of the genome.
MAI-SIM: Machine learning assisted interferometric structured illumination microscopy for everybody
Here, we present Machine learning Assisted, Interferometric Structured Illumination Microscopy, MAI-SIM, as an easy-to-implement method for fast live cell super-resolution imaging in multiple colours.
Laplacian Renormalization group for heterogeneous networks
Complex networks have been introduced as the best theoretical framework to model a large variety of physical, biological, and social systems where an intertwined pattern of interactions couples many elements.
Mendelian randomization can lead to flawed conclusions about the effects of vitamin C
A Mendelian randomization (MR) study concluded that vitamin C was not effective for pneumonia. We showed that the MR study corresponds to the comparison of two groups with similar vitamin C levels of 47.3 vs. 52.7 μM, whereas the plasma vitamin C level range in the population is from 10 to 100 μM.
