Hanjun Shin

TL;DR: This work pioneered a probabilistic approach for the generation of a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments, and provides a user-friendly software package, called PGS, which runs on local machines (for practice runs) and high-performance computing platforms.

TL;DR: Online SSA extends the conventional offline SSA by incorporating the rank-1 modification technique to incrementally update the singular spectrum of the noise model and validated the proposed method using real EEG data generated from a single channel EEG device.

TL;DR: This work proposes a new microarray integration framework that achieves high-quality integration through exploiting invariant features such as relative information among genes and shows how the proposed approach generalises the previous frameworks.

TL;DR: The proposed Online SSA extends the conventional offline SSA by incorporating the rank-1 modification technique to incrementally update the singular spectrum of the noise model, and it is shown that the algorithm does not require pre-training; it rapidly builds up an accurate noise model from initial user feed.