Grain Protein Function Prediction Based on CNN and Residual Attention Mechanism with AlphaFold2 Structure Data by Jing Liu, Xinping Zhang, Kai Huang, Yuqi Wei, Xiao Guan

“…The experimental results indicate that secondary structure and spatial structure information contribute to improving model performance. …”
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Macromolecular crystallography from an industrial perspective – the impact of synchrotron radiation on structure-based drug discovery by H. Käck, T. Sjögren

Subjects: “…structure-based drug design…”
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Structural dynamic response synthesis: A transformer-based time-series GAN approach by Sayed Ali Khodaei, Maryam Bitaraf

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The genetic structure and diversity of smallholder dairy cattle in Rwanda by Oluyinka Opoola, Felicien Shumbusho, Innocent Rwamuhizi, Isidore Houaga, David Harvey, David Hambrook, Kellie Watson, Mizeck G. G. Chagunda, Raphael Mrode, Appolinaire Djikeng

“…To assess the genetic structure and diversity of the current population, key analyses for population structure were applied: Principal Component Analysis (PCA), population structure and diversity, admixture analysis, measures of heterozygosity, runs of homozygosity (ROH) and minor allelic frequency (MAF). …”
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Relationship between population growth and socialeconomic development in the age structure perspective (on the example of Vietnam) by Thi Minh Hoa Nguyen, Ngoc Thanh Pham, Tuan Anh Ha

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SV-MeCa: an XGBoost-based meta-caller approach for structural variant calling from short-read data by Rudel Christian Nkouamedjo Fankep, Arda Söylev, Anna-Lena Kobiela, Jochen Blom, Corinna Ernst, Susanne Motameny

“…Abstract Background Calling structural variants (SVs), i.e., genomic alterations of $$\ge $$ 50bp, from whole genome short-read data remains challenging, as existing callers are known to lack accuracy and robustness. …”
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STRUCTURAL-TECTONIC MODEL OF THE BASEMENT AND SEDIMENTARY COVER OF EAST ARCTIC WATER AREAS by V. Yu. Kerimov, E. A. Lavrenova, Yu. V. Shcherbina, R. A. Mamedov

“…To discuss the question of the geological and tectonic structure of Mesozoic-Cenozoic East Arctic water areas by analysing the existing geological and geophysical data on the Arctic shelf. …”
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Longitudinal pathway analysis using structural information with case studies in early type 1 diabetes by Maria K. Jaakkola, Anu Kukkonen-Macchi, Tomi Suomi, Laura L. Elo

“…The few available methods allowing the pathway analysis of more complex study designs cannot use pathway structures or handle the situation where the variable of interest is not defined for all samples. …”
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Redefining comorbidity understanding in rheumatoid arthritis through novel approaches using real-world data by Diego Benavent, Chamaida Plasencia-Rodríguez

“…Meanwhile, natural language processing (NLP) and artificial intelligence (AI) image analysis can bridge the gap between structured and unstructured data, by extracting meaningful information from unstructured fields such as free text or imaging. …”
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Automated system for high-throughput process-structure-property dataset generation of structural materials: A γ/γ′ superalloy case study by Thomas Hoefler, Ayako Ikeda, Toshio Osada, Toru Hara, Kyoko Kawagishi, Takahito Ohmura

“…An estimated 200 times faster than conventional methods using tensile testing specimens, a complete Process-Structure-Property (P-S-P) dataset is created from a single sample. …”
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Estimating Subsurface Thermohaline Structure in the Tropical Western Pacific Using DO-ResNet Model by Xianmei Zhou, Shanliang Zhu, Wentao Jia, Hengkai Yao

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DETERMINANTS OF STRUCTURAL DIMENSION OF DAILY BEHAVIOUR IN A TRADITIONAL AFRICAN CITY: A CASE STUDY OF ILORIN, NIGERIA by Moses Olutoyin ADEDOKUN

“…The study also shows clearly that the temporal structure of activity in Ilorin is different from what obtains in Western cities where there is flexibility in the usage of time. …”
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Selecting the Number of Clusters in Mixture Multigroup Structural Equation Modeling by Andres F. Perez Alonso, Jeroen K. Vermunt, Yves Rosseel, Kim De Roover

“…Behavioral scientists often use Multigroup Structural Equation Modeling (MG-SEM) to compare groups in terms of their latent variables (LVs) relations — also called 'structural relations’. …”
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Hands-On Data Gathering by Claudia Mejía de la Pava, Silvia Manessi

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A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen by Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

“…Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. …”
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The 102–103° E geodivider in the modern lithosphere structure of Сentral Asia by Yu. G. Gatinsky, T. V. Prokhorova, D. V. Rundquist

“…According to our investigations, the 102–103° E geodivider is a regional geological-geophysical border that may be compared with the Tornquist Line, and, by its scale, with the Uralian and Appalachian fronts and some others large structures.…”
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Managerial and natural disposability in two-stage network structure: a DEA-based approach by Mahnaz Maghbouli, Azam Pourhabib Yekta

Subjects: “…data envelopment analysis (dea)…”
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The Impact of Financial Structure on Financial Security in an Emerging Market by Huong Thi Thanh Co, Cong Van Nguyen

“…This paper aims to understand the extent and trend of the impact of financial structure on the financial security of companies in an emerging economy. …”
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TRsv: simultaneous detection of tandem repeat variations, structural variations, and short indels using long read sequencing data by Shunichi Kosugi, Chikashi Terao

“…Abstract Tandem repeat copy number variations (TR-CNVs), structural variations (SVs), and short indels have been responsible for many diseases and traits, but no tools exist to distinguish and detect these variants. …”
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Tracking climate adaptation in hospitals: An inventory of structural measures by Louise Elstow, Felipe Rojas Parra, Kristen MacAskill

“…We found 125 examples of implemented structural measures intended to adapt hospital facilities to respond more favourably to anticipated changes in climate. …”
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