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Mass spectrometry (MS) is an important technique for chemical profiling which calculates for a sample a high dimensional histogram-like spectrum. A crucial step of MS data processing is the peak picking which selects peaks containing…

Machine Learning · Statistics 2009-10-05 Theodore Alexandrov , Klaus Steinhorst , Oliver Keszoecze , Stefan Schiffler

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over…

Applications · Statistics 2015-01-19 Abel Rodriguez , Scott C. Schmidler

Understanding protein dynamics are essential for deciphering protein functional mechanisms and developing molecular therapies. However, the complex high-dimensional dynamics and interatomic interactions of biological processes pose…

Quantitative Methods · Quantitative Biology 2025-05-15 Tiexin Qin , Mengxu Zhu , Chunyang Li , Terry Lyons , Hong Yan , Haoliang Li

Mass spectrometry imaging (MSI) enables label-free visualization of molecular distributions across tissue samples but generates large and complex datasets that require effective peak picking to reduce data size while preserving meaningful…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Philipp Weigand , Nikolas Ebert , Shad A. Mohammed , Denis Abu Sammour , Carsten Hopf , Oliver Wasenmüller

Much new solid state technology for single-photon sources, detectors, photovoltaics and quantum computation relies on the fabrication of strained semiconductor nanostructures. Successful development of these devices depends strongly on…

This paper presents a proof-of-concept method for classifying chemical compounds directly from NMR data without doing structure elucidation. This can help to reduce time in finding good structure candidates, as in most cases matching must…

Mass spectrometry is a widely used method to study molecules and processes in medicine, life sciences, chemistry, catalysis, and industrial product quality control, among many other applications. One of the main features of some mass…

Chemical Physics · Physics 2024-07-02 Daniil A. Boiko , Valentine P. Ananikov

Tip-Enhanced Raman Spectroscopy (TERS) provides nanoscale chemical fingerprints alongside high-resolution topographic mapping of molecules, offering a powerful tool for materials discovery. However, TERS image datasets are challenging to…

Materials Science · Physics 2026-02-24 Harshit Sethi , Markus Junttila , Orlando J Silveira , Adam S Foster

Nuclear magnetic resonance has emerged as a vital technique for investigating strongly correlated electron systems, and is particularly important for studying superconductivity. In this paper the basic features of NMR as a technique for…

Superconductivity · Physics 2009-01-26 N. J. Curro

Carbohydrates, vital components of biological systems, are well-known for their structural diversity. Nuclear Magnetic Resonance (NMR) spectroscopy plays a crucial role in understanding their intricate molecular arrangements and is…

Machine Learning · Computer Science 2023-11-22 Maria Bånkestad , Keven M. Dorst , Göran Widmalm , Jerk Rönnols

The algebraic reformulation of molecular Quantum Electrodynamics (mQED) at finite temperatures is applied to Nuclear Magnetic Resonance (NMR) in order to provide a foundation for the reconstruction of much more detailed molecular…

Quantum Physics · Physics 2020-09-25 Kolja Them

Mass spectrometry-based proteomics has become the tool of choice for identifying and quantifying the proteome of an organism. Though recent years have seen a tremendous improvement in instrument performance and the computational tools used,…

A new deep neural network based on the WaveNet architecture (WNN) is presented, which is designed to grasp specific patterns in the NMR spectra. When trained at a fixed non-uniform sampling (NUS) schedule, the WNN benefits from pattern…

Biomolecules · Quantitative Biology 2022-12-05 Amir Jahangiri , Xiao Han , Dmitry Lesovoy , Tatiana Agback , Peter Agback , Adnane Achour , Vladislav Orekhov

Protein representation learning plays a crucial role in understanding the structure and function of proteins, which are essential biomolecules involved in various biological processes. In recent years, deep learning has emerged as a…

Biomolecules · Quantitative Biology 2024-03-11 Bozhen Hu , Cheng Tan , Lirong Wu , Jiangbin Zheng , Jun Xia , Zhangyang Gao , Zicheng Liu , Fandi Wu , Guijun Zhang , Stan Z. Li

Proteins are the major building blocks of life, and actuators of almost all chemical and biophysical events in living organisms. Their native structures in turn enable their biological functions which have a fundamental role in drug design.…

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase…

Materials Science · Physics 2021-05-27 Nathan J. Szymanski , Christopher J. Bartel , Yan Zeng , Qingsong Tu , Gerbrand Ceder

Understanding the structure of a protein complex is crucial indetermining its function. However, retrieving accurate 3D structures from microscopy images is highly challenging, particularly as many imaging modalities are two-dimensional.…

Quantitative Methods · Quantitative Biology 2021-10-18 Benjamin J. Blundell , Christian Sieben , Suliana Manley , Ed Rosten , QueeLim Ch'ng , Susan Cox

Analysis of the sequence-structure relationship in RNA molecules are essential to evolutionary studies but also to concrete applications such as error-correction methodologies in sequencing technologies. The prohibitive sizes of the…

Quantitative Methods · Quantitative Biology 2013-05-31 Vladimir Reinharz , Yann Ponty , Jérôme Waldispühl

The interaction between proteins and nucleic acids is crucial for processes that sustain cellular function, including DNA maintenance and the regulation of gene expression and translation. Amino acid mutations in protein-nucleic acid…

Biomolecules · Quantitative Biology 2025-12-01 Somnath Mondal , Tinkal Mondal , Soumajit Pramanik , Rukmankesh Mehra

Boundary incompleteness raises great challenges to automatic prostate segmentation in ultrasound images. Shape prior can provide strong guidance in estimating the missing boundary, but traditional shape models often suffer from hand-crafted…

Computer Vision and Pattern Recognition · Computer Science 2016-12-07 Xin Yang , Lequan Yu , Lingyun Wu , Yi Wang , Dong Ni , Jing Qin , Pheng-Ann Heng
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