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PEMT: a patent enrichment tool for drug discovery (vol 39, btac716, 2023)

BIOINFORMATICS 2023年第12期39卷 btac716-btac716页

作者： Gadiya, Yojana Zaliani, Andrea Gribbon, Philip Hofmann-Apitius, Martin Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP) Hamburg 22525 Germany Fraunhofer Cluster of Excellence for Immune-Mediated Diseases (CIMD) Frankfurt 60590 Germany Department of Bioinformatics Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Sankt Augustin 53754 Germany Bonn-Aachen International Center for Information Technology (B-IT) University of Bonn Bonn 53113 Germany

Motivation Drug discovery practitioners in industry and academia use semantic tools to extract information from online scientific literature to generate new insights into targets, therapeutics and diseases. However, due to complexities in access and analysis, patent-based literature is often overlooked as a source of information. As drug discovery is a highly competitive field, naturally, tools that tap into patent literature can provide any actor in the field an advantage in terms of better informed decision-making. Hence, we aim to facilitate access to patent literature through the creation of an automatic tool for extracting information from patents described in existing public *** Here, we present PEMT, a novel patent enrichment tool, that takes advantage of public databases like ChEMBL and SureChEMBL to extract relevant patent information linked to chemical structures and/or gene names described through FAIR principles and metadata annotations. PEMT aims at supporting drug discovery and research by establishing a patent landscape around genes of interest. The pharmaceutical focus of the tool is mainly due to the subselection of International Patent Classification codes, but in principle, it can be used for other patent fields, provided that a link between a concept and chemical structure is investigated. Finally, we demonstrate a use-case in rare diseases by generating a gene-patent list based on the epidemiological prevalence of these diseases and exploring their underlying patent *** and implementation PEMT is an open-source Python tool and its source code and PyPi package are available at https://***/Fraunhofer-ITMP/PEMT and https://***/project/PEMT/, *** information Supplementary data are available at Bioinformatics online.

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Graph Visualization for Blockchain Data

arXiv

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arXiv 2024年

作者： Dietl, Marcell Gemünd, Andre Oeltz, Daniel Thiele, Felix M. Werner, Christian Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin53757 Germany frontmark GmbH Taunusstraße 63 Wiesbaden65183 Germany

In this report, we introduce a novel approach to visualize extremely large graphs efficiently. Our method combines two force-directed algorithms, Kamada-Kawai and ForceAtlas2, to handle different graph components based on their node count. Additionally, we suggest utilizing the Fast Multipole method to enhance the speed of ForceAtlas2. Although initially designed for analyzing bitcoin transaction graphs, for which we present results here, this algorithm can also be applied to other crypto currency transaction graphs or graphs from diverse domains. Copyright © 2024, The Authors. All rights reserved.

关键词： Directed graphs

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Parameterized Neural Networks for Finance

arXiv

引用

arXiv 2023年

作者： Oeltz, Daniel Hamaekers, Jan Pilz, Kay F. Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin53757 Germany Kinetic Mind GmbH Germany

We discuss and analyze a neural network architecture, that enables learning a model class for a set of different data samples rather than just learning a single model for a specific data sample. In this sense, it may help to reduce the overfitting problem, since, after learning the model class over a larger data sample consisting of such different data sets, just a few parameters need to be adjusted for modeling a new, specific problem. After analyzing the method theoretically and by regression examples for different one-dimensional problems, we finally apply the approach to one of the standard problems asset managers and banks are facing: the calibration of spread curves. The presented results clearly show the potential that lies within this method. Furthermore, this application is of particular interest to financial practitioners, since nearly all asset managers and banks which are having solutions in place may need to adapt or even change their current methodologies when ESG ratings additionally affect the bond spreads. Copyright © 2023, The Authors. All rights reserved.

关键词： Network architecture

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Integrating Cloud computing, Bayesian Optimization, and Neural-Additive Modeling for Enhanced CAM Systems in 5-Axis Milling 34

Integrating Cloud Computing, Bayesian Optimization, and Neur...

引用

34th CIRP Design Conference, CIRP 2024

作者： Rudel, Viktor Vinogradov, Georg Ganser, Philipp Bergs, Thomas Vahl, Christopher Frings, Markus König, Valentina Schambach, Maximilian Dietzel, Stefan Königs, Michael Fraunhofer Institute for Production Technology IPT Steinbachstraße 17 Aachen52074 Germany RWTH Aachen University Campus-Boulevard 30 Aachen52074 Germany Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven 1 Sankt Augustin53757 Germany ModuleWorks GmbH Henricistraße 50 Aachen52072 Germany Merantix Momentum Merantix AI Campus Max-Urich-Straße 3 Berlin13355 Germany EXAPT Systemtechnik GmbH Theaterstraße 12 Aachen52062 Germany

This publication introduces the development and application of an advanced CAD/CAM/CAE system that leverages the computational capabilities of an edge-cloud infrastructure. The developed system consists of containerized technology models for various complex process planning simulation tasks in 5-axis-milling, such as toolpath calculation, cutter-workpiece-engagement, uncut chip geometry or cutting force simulations. Moreover, a Bayesian optimization (BO) algorithm is coupled with the system enabling multi-objective optimizations of the considered machining operations by varying predefined CAM-parameters. The result of the optimization consists of a set of Pareto-efficient solutions. Each solution realizes a different tradeoff between the technological objectives of the process planner. Since mastering the complexity of the design space is a major challenge in today's CAM programming workflow, a Neural-Additive Model (NAM) is coupled with the system improving guided search through the configuration/result space. This reduces the convergence time to an optimal CAM parameter set. The coupling of the cloud computing, multi-objective optimization and artificial intelligence method with a CAM-kernel is demonstrated based on the process design of 5-axis milling operations for a blade-integrated disk (blisk). © 2024 The Authors. Published by Elsevier B.V.

关键词： Milling (machining)

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Fault Detection in Uni-Directional Tape Production Using Image Processing 25th

Fault Detection in Uni-Directional Tape Production Using Ima...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Devagekar, Somesh Delforouzi, Ahmad Plöger, Paul G. Department of Computer Science Hochschule Bonn-Rhein-Sieg Bonn Germany Institute for Algorithms and Scientific Computing Fraunhofer SCAI Bonn Germany

ISBN: (纸本)9783030687984

The quality of uni-directional tape in its production process is affected by environmental conditions like temperature and production speed. In this paper, computer vision algorithms on the scanned images are needed to be used in this context to detect and classify tape damages during the manufacturing procedure. We perform a comparative study among famous feature descriptors for fault candidate generation, then propose own features for fault detection. We investigate various machine learning techniques to find best model for the classification problem. The empirical results demonstrate the high performance of the proposed system and show preference of random forest and canny edges for classifier and feature generator respectively. © 2021, Springer Nature Switzerland AG.

关键词： Feature extraction

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QR Factorization of Block Low-Rank Matrices on Multi-instance GPU 23rd

QR Factorization of Block Low-Rank Matrices on Multi-insta...

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23rd International Conference on Parallel and Distributed computing, Applications, and Technologies, PDCAT 2022

作者： Ohshima, Satoshi Ida, Akihiro Yokota, Rio Yamazaki, Ichitaro Information Technology Center Nagoya University Aichi Japan Research Institute for Value-Added-Information Generation Japan Agency for Marine-Earth Science and Technology Kanagawa Japan Global Scientific Information and Computing Center Tokyo Institute of Technology Tokyo Japan Scalable Algorithms Department Sandia National Laboratories New Mexico United States

ISBN: (纸本)9783031299261

The QR factorization, which is a fundamental operation in linear algebra, is used extensively in scientific simulations. The acceleration and memory reduction of it are important research targets. QR factorization using block low-rank matrices (BLR-QR) has previously been proposed to address this issue. In this study, we consider its implementation on a GPU. Current CPUs and GPUs have numerous computational cores and the performance consists of the total performance of them. Therefore, the degree of parallelism of the target calculation is important for obtaining high performance. By contrast, many applications, including BLR-QR, do not have sufficient parallelism. Batched computation has attracted attention for achieving high performance in such calculations. However, the use of it requires major code rewriting and is extremely laborious. Thus, we propose the use of the multi-instance GPU (MIG) feature of current GPUs. Using MIG, we succeeded in obtaining a 53.3% time reduction over the CPU and 77.6% over the GPU without MIG. From the above result, we succeeded in demonstrating rapid implementation of BLR-QR on MIG and usefulness of MIG. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphics processing unit

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Generalized Sparse Grid Interpolation Based on the Fast Discrete Fourier Transform 1

引用

5th Workshop on Sparse Grids and Applications, SGA 2018

作者： Griebel, Michael Hamaekers, Jan Institute for Numerical Simulation University of Bonn Bonn Germany Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin Germany

ISBN: (数字)9783030813628

ISBN: (纸本)9783030813611

In (Griebel and Hamaekers, Fast discrete Fourier transform on generalized sparse grids, Sparse grids and Applications, volume 97 of Lecture Notes in Computational Science and Engineering, pages 75–108, Springer, 2014), an algorithm for trigonometric interpolation involving only so-called standard information of multivariate functions on generalized sparse grids has been suggested and a study on its application for the interpolation of functions in periodic Sobolev spaces of dominating mixed smoothness has been presented. In this complementary paper, we now give a slight modification of the proofs, which yields an extension from the pairing (Hs,Hmixt) to the more general pairing (Hs,Hmixt,r) and which in addition results in an improved estimate for the interpolation error. The improved (constructive) upper bound is in particular consistent with the lower bound for sampling on regular sparse grids with r = 0 and s = 0 given in (Dũng, Acta Mathematica Vietnamica, 43(1):83–110, 2018;Dũng et al., Hyperbolic Cross Approximation, Advanced Courses in Mathematics - CRM Barcelona, Birkhäuser/Springer, 2018). © 2021, Springer Nature Switzerland AG.

关键词： Discrete Fourier transforms

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A Framework for Synthetic Power System Dynamics

arXiv

引用

arXiv 2023年

作者： Büttner, Anna Plietzsch, Anton Anvari, Mehrnaz Hellmann, Frank Potsdam-Institute for Climate Impact Research Germany Fraunhofer Research Institution for Energy Infrastructures and Geothermal Systems Germany Fraunhofer Institute for Algorithms and Scientific Computing Germany

We present a modular framework for generating synthetic power grids that considers the heterogeneity of real power grid dynamics but remains simple and tractable. This enables the generation of large sets of synthetic grids for a wide range of applications. For the first time, our synthetic model also includes the major drivers of fluctuations on short-time scales and a set of validators that ensure the resulting system dynamics are plausible. The synthetic grids generated are robust and show good synchronization under all evaluated scenarios, as should be expected for realistic power grids. A software package that includes an efficient Julia implementation of the framework is released as a companion to the paper. © 2023, CC BY.

关键词： System theory

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PERTURBATIONS OF EMBEDDED EIGENVALUES OF ASYMPTOTICALLY PERIODIC MAGNETIC SCHRÖDINGER OPERATORS ON A CYLINDER

arXiv

引用

arXiv 2025年

作者： Jansen, Jonas Sasane, Sara Maad Treschow, Wilhelm Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin53757 Germany Centre for Mathematical Sciences Lund University P.O. Box 118 Lund221 00 Sweden

We investigate the persistence of embedded eigenvalues for a class of magnetic Laplacians on an infinite cylindrical domain. The magnetic potential is assumed to be C2 and asymptotically periodic along the unbounded direction, with an algebraic decay rate towards a periodic background potential. Under the condition that the embedded eigenvalue of the unperturbed operator lies away from the thresholds of the continuous spectrum, we show that the set of nearby potentials for which the embedded eigenvalue persists forms a smooth manifold of finite and even codimension. The proof employs tools from Floquet theory, exponential dichotomies, and Lyapunov–Schmidt reduction. Additionally, we give an example of a potential which satisfies the assumptions of our main *** Codes 35P05, 47A55, 81Q15, 35B20, 35J10, 35J15, 81Q10 Copyright © 2025, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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On Multilevel Energy-Based Fragmentation Methods

arXiv

引用

arXiv 2024年

作者： Barker, James Griebel, Michael Hamaekers, Jan Institute for Numerical Simulation University of Bonn Friedrich-Hirzebruch-Allee 7 Bonn53115 Germany Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven 1 Sankt Augustin53757 Germany

Energy-based fragmentation methods approximate the potential energy of a molecular system as a sum of contribution terms built from the energies of particular subsystems. Some such methods reduce to truncations of the many-body expansion (MBE);others combine subsystem energies in a manner inspired by the principle of inclusion/exclusion (PIE). The combinatorial technique of Möbius inversion of sums over partially ordered sets, which generalizes the PIE, is known to provide a non-recursive expression for the MBE contribution terms, and has also been connected to related cluster expansion methods. We build from these ideas a very general framework for decomposing potential functions into energetic contribution terms associated with elements of particular partially ordered sets (posets) and direct products thereof. Specific choices immediately reproduce not only the MBE, but also a number of other existing decomposition forms, including, e.g., the multilevel ML-BOSSANOVA schema. Furthermore, a different choice of poset product leads to a setup familiar from the combination technique for high-dimensional approximation, which has a known connection to quantum-chemical composite methods. We present the ML-SUPANOVA decomposition form, which allows the further refinement of the terms of an MBE-like expansion of the Born-Oppenheimer potential according to systematic hierarchies of ab initio methods and of basis sets. We outline an adaptive algorithm for the a posteori construction of quasi-optimal truncations of this decomposition. Some initial experiments are reported and *** Codes 35J10, 65D40, 65Z05, 92E10, 06A07 © 2024, CC BY.

关键词： Adaptive algorithms

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