In membrane proteins, symmetry and pseudosymmetry often have functional or evolutionary implications. However, available symmetry detection methods have not been tested systematically on this class of proteins because of the lack of an appropriate benchmark set. Here we present MemSTATS, a publicly available benchmark set of both quaternary- and internal-symmetries in membrane protein structures. The symmetries are described in terms of order, repeated elements, and orientation of the axis with respect to the membrane plane. Moreover, using MemSTATS, we compare the performance of four widely used symmetry detection algorithms and highlight specific challenges and areas for improvement in the future.
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http://dx.doi.org/10.1016/j.jmb.2019.09.020 | DOI Listing |
Bioinformatics
January 2025
Department of Statistics, University of Oxford, St Giles', Oxford, OX1 3LB, United Kingdom.
Motivation: Machine learning-based scoring functions (MLBSFs) have been found to exhibit inconsistent performance on different benchmarks and be prone to learning dataset bias. For the field to develop MLBSFs that learn a generalisable understanding of physics, a more rigorous understanding of how they perform is required.
Results: In this work, we compared the performance of a diverse set of popular MLBSFs (RFScore, SIGN, OnionNet-2, Pafnucy, and PointVS) to our proposed baseline models that can only learn dataset biases on a range of benchmarks.
J Chem Theory Comput
January 2025
Qingdao Institute for Theoretical and Computational Sciences and Center for Optics Research and Engineering, Shandong University, Qingdao 266237, China.
Given a number of data sets for evaluating the performance of single reference methods for the low-lying excited states of closed-shell molecules, a comprehensive data set for assessing the performance of multireference methods for the low-lying excited states of open-shell systems is still lacking. For this reason, we propose an extension (QUEST#4X) of the radical subset of QUEST#4 ( , , 3720) to cover 110 doublet and 39 quartet excited states. Near-exact results obtained by iterative configuration interaction with selection and second-order perturbation correction (iCIPT2) are taken as benchmark to calibrate static-dynamic-static configuration interaction (SDSCI) and static-dynamic-static second-order perturbation theory (SDSPT2), which are minimal MRCI and CI-like perturbation theory, respectively.
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February 2025
Department of Orthopaedic Surgery, New York-Presbyterian Hospital/Columbia University Medical Center, New York, NY, USA.
Background: Reverse total shoulder arthroplasty (rTSA) demonstrates favorable long-term data and has outpaced anatomic total shoulder arthroplasty and hemiarthroplasty as the most-performed shoulder arthroplasty procedure. As indications and outcomes continue to favor rTSA, patients may turn to the internet as an efficient modality to answer various questions or concerns. This study investigates online patient questions pertaining to rTSA and the quality of the websites providing information.
View Article and Find Full Text PDFDigit Health
January 2025
Department of Computer Science, School of Systems and Technology, University of Management and Technology, Lahore, Pakistan.
Objective: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition influenced by various genetic and environmental factors. Currently, there is no definitive clinical test, such as a blood analysis or brain scan, for early diagnosis. The objective of this study is to develop a computational model that predicts ASD driver genes in the early stages using genomic data, aiming to enhance early diagnosis and intervention.
View Article and Find Full Text PDFFront Artif Intell
January 2025
School of Engineering, Institute of Computer Science, Intelligent Information Systems Research Group, Zurich University of Applied Sciences, Winterthur, Switzerland.
Many different methods for prompting large language models have been developed since the emergence of OpenAI's ChatGPT in November 2022. In this work, we evaluate six different few-shot prompting methods. The first set of experiments evaluates three frameworks that focus on the quantity or type of shots in a prompt: a baseline method with a simple prompt and a small number of shots, random few-shot prompting with 10, 20, and 30 shots, and similarity-based few-shot prompting.
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