Related papers: SCN as a Local Probe of Protein Structural Dynamic…
The spectrum and scale of fluctuations in protein structures affect the range of cell phenomena, including stability of protein structures or their fragments, allosteric transitions and energy transfer. The study presents a…
We propose a combined experimental (Atomic Force Microscopy) and theoretical study of the structural and dynamical properties of nucleosomes. In contrast to biochemical approaches, this method allows to determine simultaneously the DNA…
In this article, we discuss metal-protein interactions in the Ag-lysozyme complex by spectroscopic measurements. The analysis of the variation in relative intensities of SERS bands reveal the orientation and the change in conformation of…
We propose a location-adaptive self-normalization (SN) based test for change points in time series. The SN technique has been extensively used in change-point detection for its capability to avoid direct estimation of nuisance parameters.…
Advanced nanopore measurements allow structural probing of molecules with high spatial and temporal resolution. We report high signal-to-noise, 1-10 MHz bandwidth, translocation measurements of the multi-state folding of heme protein…
We theoretically study ambient pressure superconductivity in thin films of La$_3$Ni$_2$O$_7$. We construct model Hamiltonians adopting the crystal structure theoretically determined by fixing the in-plane lattice constant to those…
Superconductivity in strontium titanate has remained enigmatic for more than 50 years. The LaAlO$_3$/SrTiO$_3$ (LAO/STO) heterointerface enables systematic dimensional confinement, from a two-dimensional electron gas to…
Label noise is pervasive in various real-world scenarios, posing challenges in supervised deep learning. Deep networks are vulnerable to such label-corrupted samples due to the memorization effect. One major stream of previous methods…
Attention-based transformers have played an important role in wireless sensor network (WSN) timing anomaly detection due to their ability to capture long-term dependencies. However, there are several issues that must be addressed, such as…
More than twenty years ago, scientists succeeded in pushing the limits of optical detection to single molecules using fluorescence. This breakthrough has revolutionized biophysical measurements, but restrictions in photophysics and labeling…
This paper focuses on three critical problems on protein classification. Firstly, Carbohydrate-active enzyme (CAZyme) classification can help people to understand the properties of enzymes. However, one CAZyme may belong to several classes.…
The detection of similarities between long DNA and protein sequences is studied using concepts of statistical physics. It is shown that mutual similarities can be detected by sequence alignment methods only if their amount exceeds a…
Aluminum scandium nitride (AlScN) ferroelectrics are promising for next-generation non-volatile memory applications due to high remnant polarization compared with Pb(ZrxTi1-x)O3 and doped-HfO2 material systems, as well as their fast…
The lattice properties at low temperatures of two samples of NdFeAsO1-xFx (x=0.05 and 0.25) have been examined in order to investigate possible structural phase transition that may occur in the optimally doped superconducting sample with…
In conventional remote sensing change detection (RS CD) procedures, extensive manual labeling for bi-temporal images is first required to maintain the performance of subsequent fully supervised training. However, pixel-level labeling for CD…
Two novel reduced dimensionality (RD) experiments -(4,3)D-hNCOcaNH and (4,3)D-hNcoCANH- have been presented here to facilitate the backbone resonance assignment of proteins both in terms of its accuracy and speed. The experiments basically…
While mislabeled or ambiguously-labeled samples in the training set could negatively affect the performance of deep models, diagnosing the dataset and identifying mislabeled samples helps to improve the generalization power. Training…
In protein secondary structure prediction, each amino acid in sequence is typically treated as a distinct category and represented by a one-hot vector. In this study, we developed two novel chemical representations for amino acids utilizing…
High-quality training datasets are crucial for the development of effective protein design models, but existing synthetic datasets often include unfavorable sequence-structure pairs, impairing generative model performance. We leverage…
The formalism for computing the signal-to-noise ratio (SNR) for laser radar is reviewed and applied to the tasks of target detection, direction-finding, and phase change estimation with squeezed light. The SNR for heterodyne detection of…