Suchergebnisse - jana and python source code*

Marginalizing Sample Consensus.

Autoren: Barath, Daniel Noskova, Jana Matas, Jiri

Quelle: IEEE Transactions on Pattern Analysis & Machine Intelligence. Nov2022, Vol. 44 Issue 11, p8420-8432. 13p.

Schlagwörter: *C++, *DECISION making, *ALGORITHMS, SOURCE code, PYTHON programming language

Guide assignment in single-cell CRISPR screens using crispat.

Autoren: Braunger, Jana M Velten, Britta

Quelle: Bioinformatics; Sep2024, Vol. 40 Issue 9, p1-6, 6p

Schlagwörter: GENETIC engineering, FUNCTIONAL genomics, CRISPRS, SOURCE code, MEDICAL screening

Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data.

Autoren: Idkowiak, Jakub Dehairs, Jonas Schwarzerová, Jana et al.

Quelle: Nature Communications; 9/30/2025, Vol. 16 Issue 1, p1-19, 19p

Schlagwörter: LIPIDOMICS, METABOLOMICS, MASS spectrometry, PYTHON programming language, MATHEMATICAL statistics, VISUALIZATION, DATA analysis, PROGRAMMING languages

deepFPlearn⁺: enhancing toxicity prediction across the chemical universe using graph neural networks.

Autoren: Soulios, Kyriakos Scheibe, Patrick Bernt, Matthias et al.

Quelle: Bioinformatics; Dec2023, Vol. 39 Issue 12, p1-4, 4p

Schlagwörter: CHEMICAL testing, MOLECULAR structure, SOFTWARE compatibility, MOLECULAR weights, SOURCE code

pyCapsid: identifying dominant dynamics and quasi-rigid mechanical units in protein shells.

Autoren: Brown, Colin Agarwal, Anuradha Luque, Antoni

Quelle: Bioinformatics; Jan2024, Vol. 40 Issue 1, p1-5, 5p

Schlagwörter: SOURCE code, PROTEINS, CAPSIDS, PYTHONS

Firma/Körperschaft: MASSACHUSETTS Institute of Technology

Source code and example data for the paper: 'Magmatism Controls Global Oceanic Transform Fault Topography'

Autoren: Tian, Xiaochuan Behn, Mark Ito, Garrett et al.

Open-Source Web Service with Morphological Dictionary-Supplemented Deep Learning for Morphosyntactic Analysis of Czech

Autoren: Straka, Milan Straková, Jana

Index Begriffe: Computer Science - Computation and Language, text

URL: http://arxiv.org/abs/2406.12422

Reproducibility of density functional approximations: How new functionals should be reported.

Autoren: Lehtola, Susi Marques, Miguel A. L.

Quelle: Journal of Chemical Physics; 9/21/2023, Vol. 159 Issue 11, p1-14, 14p

Schlagwörter: FUNCTIONALS, DENSITY functional theory, DENSITY, NUMERICAL calculations, SOURCE code

An empirical study on the effectiveness of large language models for binary code understanding.

Autoren: Shang, Xiuwei Fu, Zhenkan Cheng, Shaoyin et al.

Quelle: Empirical Software Engineering; Feb2026, Vol. 31 Issue 1, p1-38, 38p

A comparison of large language models and model-driven reverse engineering for reverse engineering.

Autoren: Siala, Hanan Lano, Kevin

Quelle: Frontiers in Computer Science; 2025, p1-14, 14p

Accountability in Code Review: The Role of Intrinsic Drivers and the Impact of LLMs.

Autoren: Alami, Adam Jensen, Victor Ernst, Neil

Quelle: ACM Transactions on Software Engineering & Methodology; Nov2025, Vol. 34 Issue 8, p1-44, 44p

Schlagwörter: COMPUTER software development, LANGUAGE models, ORGANIZATIONAL accountability, INCENTIVE (Psychology), GOVERNMENT accountability, ARTIFICIAL intelligence, PROFESSIONAL peer review, SOCIAL systems

A Review of Deep Learning-Based Binary Code Similarity Analysis.

Autoren: Du, Jiang Wei, Qiang Wang, Yisen et al.

Quelle: Electronics (2079-9292); Nov2023, Vol. 12 Issue 22, p4671, 18p

Schlagwörter: BINARY codes, DEEP learning, SOFTWARE engineering, ARTIFICIAL intelligence, COMPUTER network security, SOURCE code

Benchmarking WebAssembly for Embedded Systems.

Autoren: MORON, KONARD WALLENTOWITZ, STEFAN

Quelle: ACM Transactions on Architecture & Code Optimization; Sep2025, Vol. 22 Issue 3, p1-21, 21p

RareLink: scalable REDCap-based framework for rare disease interoperability linking international registries to FHIR and Phenopackets.

Autoren: Graefe, Adam S. L. Rehburg, Filip Alkarkoukly, Samer et al.

Quelle: NPJ Genomic Medicine; 11/18/2025, Vol. 10 Issue 1, p1-11, 11p

VexIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similarity.

Autoren: VenkataKeerthy, S. Banerjee, Soumya Dey, Sayan et al.

Quelle: ACM Transactions on Software Engineering & Methodology; Nov2025, Vol. 34 Issue 8, p1-54, 54p

Schlagwörter: MALWARE, FLOWGRAPHS, FEATURE extraction, SOFTWARE frameworks

SBMLDiagrams: a python package to process and visualize SBML layout and render.

Autoren: Xu, Jin Jiang, Jessie Sauro, Herbert M

Quelle: Bioinformatics; Jan2023, Vol. 39 Issue 1, p1-2, 2p

Schlagwörter: PYTHON programming language, BIOCHEMICAL models, PDF (Computer file format), SYSTEMS biology, SOURCE code

Open-Source Web Service with Morphological Dictionary–Supplemented Deep Learning for Morphosyntactic Analysis of Czech

Autoren: Milan Straka Jana Straková

Quelle: Lecture Notes in Computer Science ISBN: 9783031705625

Schlagwörter: FOS: Computer and information sciences, Computer Science - Computation and Language, 15. Life on land, Computation and Language (cs.CL), 3. Good health

Zugangs-URL: http://arxiv.org/abs/2406.12422

Bridging the Gap: A Survey and Classification of Research-Informed Ethical Hacking Tools.

Autoren: Modesti, Paolo Golightly, Lewis Holmes, Louis et al.

Quelle: Journal of Cybersecurity & Privacy; Sep2024, Vol. 4 Issue 3, p410-448, 39p

Schlagwörter: PENETRATION testing (Computer security), SOURCE code, COMPUTER software, CLASSIFICATION, SURVEYS

All-atom protein sequence design using discrete diffusion models.

Autoren: Villegas-Morcillo, Amelia Admiraal, Gijs J. Reinders, Marcel J. T. et al.

Quelle: Journal of Cheminformatics; 12/1/2025, Vol. 18 Issue 1, p1-15, 15p

Schlagwörter: PROTEIN engineering, AMINO acids, POST-translational modification, STOCHASTIC models

Georeferenced Sediment and Surface Water Element Concentrations in the Coastal Liepāja Lake (Latvia), 2024.

Autoren: Grinfelde, Inga Valainis, Uldis Nitcis, Maris et al.

Quelle: Data (2306-5729); Dec2025, Vol. 10 Issue 12, p200, 10p

Schlagwörter: SEDIMENT analysis, TRACE elements, POLLUTION measurement, BODIES of water, LAKES, ENVIRONMENTAL monitoring, GEOSPATIAL data

Geografische Kategorien: LATVIA