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Institution

University of Basel

EducationBasel, Basel-Stadt, Switzerland
About: University of Basel is a education organization based out in Basel, Basel-Stadt, Switzerland. It is known for research contribution in the topics: Population & Transplantation. The organization has 25084 authors who have published 52975 publications receiving 2388002 citations. The organization is also known as: Universität Basel & Basel University.


Papers
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Journal ArticleDOI
TL;DR: The PhysNet-PES model as discussed by the authors predicts energy, forces, and dipole moments of chemical systems using deep neural networks (DNNs) and achieves state-of-the-art performance.
Abstract: In recent years, machine learning (ML) methods have become increasingly popular in computational chemistry. After being trained on appropriate ab initio reference data, these methods allow for accurately predicting the properties of chemical systems, circumventing the need for explicitly solving the electronic Schrodinger equation. Because of their computational efficiency and scalability to large data sets, deep neural networks (DNNs) are a particularly promising ML algorithm for chemical applications. This work introduces PhysNet, a DNN architecture designed for predicting energies, forces, and dipole moments of chemical systems. PhysNet achieves state-of-the-art performance on the QM9, MD17, and ISO17 benchmarks. Further, two new data sets are generated in order to probe the performance of ML models for describing chemical reactions, long-range interactions, and condensed phase systems. It is shown that explicitly including electrostatics in energy predictions is crucial for a qualitatively correct description of the asymptotic regions of a potential energy surface (PES). PhysNet models trained on a systematically constructed set of small peptide fragments (at most eight heavy atoms) are able to generalize to considerably larger proteins like deca-alanine (Ala10): The optimized geometry of helical Ala10 predicted by PhysNet is virtually identical to ab initio results (RMSD = 0.21 A). By running unbiased molecular dynamics (MD) simulations of Ala10 on the PhysNet-PES in gas phase, it is found that instead of a helical structure, Ala10 folds into a "wreath-shaped" configuration, which is more stable than the helical form by 0.46 kcal mol-1 according to the reference ab initio calculations.

527 citations

Journal ArticleDOI
TL;DR: Using three-dimensional correlative light and electron microscopy of Lewy bodies and Lewy neurites in postmortem brains of Parkinson’s disease patients, researchers show that the major constituents are membranes rather than proteinaceous filaments.
Abstract: Parkinson’s disease, the most common age-related movement disorder, is a progressive neurodegenerative disease with unclear etiology. Key neuropathological hallmarks are Lewy bodies and Lewy neurites: neuronal inclusions immunopositive for the protein α-synuclein. In-depth ultrastructural analysis of Lewy pathology is crucial to understanding pathogenesis of this disease. Using correlative light and electron microscopy and tomography on postmortem human brain tissue from Parkinson’s disease brain donors, we identified α-synuclein immunopositive Lewy pathology and show a crowded environment of membranes therein, including vesicular structures and dysmorphic organelles. Filaments interspersed between the membranes and organelles were identifiable in many but not all α-synuclein inclusions. Crowding of organellar components was confirmed by stimulated emission depletion (STED)-based super-resolution microscopy, and high lipid content within α-synuclein immunopositive inclusions was corroborated by confocal imaging, Fourier-transform coherent anti-Stokes Raman scattering infrared imaging and lipidomics. Applying such correlative high-resolution imaging and biophysical approaches, we discovered an aggregated protein–lipid compartmentalization not previously described in the Parkinsons’ disease brain.

527 citations

Journal ArticleDOI
01 Jun 2007-Blood
TL;DR: The results of this study offer for the first time a comprehensive and quantitative profile of miRNA expression in CLL and their healthy counterpart, suggesting that miRNAs could play a primary role in the disease itself.

526 citations

Journal ArticleDOI
Anna Seelig1
TL;DR: It is suggested that a set of well-defined structural elements is required for an interaction with P-glycoprotein, and a high percentage of amino acids with hydrogen bonding donor side chains is found in the transmembrane sequences of P- glycoprotein relevant for substrate interaction.
Abstract: P-glycoprotein actively transports a wide variety of chemically diverse compounds out of the cell. Based on a comparison of a hundred compounds previously tested as P-glycoprotein substrates, we suggest that a set of well-defined structural elements is required for an interaction with P-glycoprotein. The recognition elements are formed by two (type I unit) or three electron donor groups (type II unit) with a fixed spatial separation. Type I units consist of two electron donor groups with a spatial separation of 2.5 +/- 0.3 A. Type II units contain either two electron donor groups with a spatial separation of 4.6 +/- 0.6 A or three electron donor groups with a spatial separation of the outer two groups of 4.6 +/- 0.6 A. All molecules that contain at least one type I or one type II unit are predicted to be P-glycoprotein substrates. The binding to P-glycoprotein increases with the strength and the number of electron donor or hydrogen bonding acceptor groups forming the type I and type II units. Correspondingly, a high percentage of amino acids with hydrogen bonding donor side chains is found in the transmembrane sequences of P-glycoprotein relevant for substrate interaction. Molecules that minimally contain one type II unit are predicted to be inducers of P-glycoprotein over-expression.

526 citations

Journal ArticleDOI
A. Abada1, Marcello Abbrescia2, Marcello Abbrescia3, Shehu S. AbdusSalam4  +1491 moreInstitutions (239)
TL;DR: In this article, the authors present the second volume of the Future Circular Collider Conceptual Design Report, devoted to the electron-positron collider FCC-ee, and present the accelerator design, performance reach, a staged operation scenario, the underlying technologies, civil engineering, technical infrastructure, and an implementation plan.
Abstract: In response to the 2013 Update of the European Strategy for Particle Physics, the Future Circular Collider (FCC) study was launched, as an international collaboration hosted by CERN. This study covers a highest-luminosity high-energy lepton collider (FCC-ee) and an energy-frontier hadron collider (FCC-hh), which could, successively, be installed in the same 100 km tunnel. The scientific capabilities of the integrated FCC programme would serve the worldwide community throughout the 21st century. The FCC study also investigates an LHC energy upgrade, using FCC-hh technology. This document constitutes the second volume of the FCC Conceptual Design Report, devoted to the electron-positron collider FCC-ee. After summarizing the physics discovery opportunities, it presents the accelerator design, performance reach, a staged operation scenario, the underlying technologies, civil engineering, technical infrastructure, and an implementation plan. FCC-ee can be built with today’s technology. Most of the FCC-ee infrastructure could be reused for FCC-hh. Combining concepts from past and present lepton colliders and adding a few novel elements, the FCC-ee design promises outstandingly high luminosity. This will make the FCC-ee a unique precision instrument to study the heaviest known particles (Z, W and H bosons and the top quark), offering great direct and indirect sensitivity to new physics.

526 citations


Authors

Showing all 25374 results

NameH-indexPapersCitations
Yang Yang1712644153049
Martin Karplus163831138492
Frank J. Gonzalez160114496971
Paul Emery1581314121293
Matthias Egger152901184176
Don W. Cleveland15244484737
Ashok Kumar1515654164086
Kurt Wüthrich143739103253
Thomas J. Smith1401775113919
Robert Huber13967173557
Peter Robmann135143897569
Ernst Detlef Schulze13367069504
Michael Levine12958655963
Claudio Santoni129102780598
Pablo Garcia-Abia12698978690
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023146
2022552
20213,395
20203,227
20192,984
20182,775