Showing 1,321 - 1,340 results of 14,077 for search '"Genetics"', query time: 0.08s Refine Results
  1. 1321

    Quantifying the regulatory potential of genetic variants via a hybrid sequence-oriented model with SVEN by Yu Wang, Nan Liang, Ge Gao

    Published 2024-12-01
    “…Understanding the transcription effects of noncoding genetic variants are still major unsolved problems, which is critical for downstream applications in human genetics and precision medicine. …”
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    Article
  2. 1322

    Binary phase-coded radar waveform optimization based on improved hybrid quantum genetic algorithm by Yu ZHANG, Jing ZHAO, Yanguo JIA, Xiumin SHEN

    Published 2024-01-01
    “…To overcome the problem of single search focus and limited application scope of existing algorithm, a binary phase-coded radar waveform optimization (RWO) based on improved hybrid quantum genetic algorithm (IHQGA) was proposed.IHQGA adopted a novel self-adaptive rotation angle strategy, which dynamically adjusted the rotation angle based on evolutionary process and cosine similarity.The convergence speed, global search capability, and solution quality were improved.Simulation results demonstrate that compared with genetic algorithms, basic quantum genetic algorithms, and hybrid quantum genetic algorithms, IHQGA performs better in terms of solution quality and resource consumption for six benchmark functions that include single-peak, multi-peak, and non-convex optimization problems.Additionally, for binary phase-coded RWO, which verifies the feasibility and effectiveness of IHQGA in WO.…”
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  3. 1323
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  5. 1325

    Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm by Yao Ya-feng, Lin Jian, Ge Jian, Peng Shi-long, Yin Jian-chao, Ouyang Li-na

    Published 2021-01-01
    “…Based on the niche principle, the traditional genetic algorithm is updated by the fuzzy random method, and the improved niche genetic algorithm is proposed. …”
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    Article
  6. 1326
  7. 1327

    Why have tobacco control policies stalled? Using genetic moderation to examine policy impacts. by Jason M Fletcher

    Published 2012-01-01
    “…<h4>Conclusions</h4>This study provides novel evidence of "gene-policy" interaction and suggests a genetic mechanism for the large differences in response to tobacco policies. …”
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    Article
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  10. 1330

    A Co-Evolutionary Genetic Algorithm Approach to Optimizing Deep Learning for Brain Tumor Classification by Abdelmgeid A. Ali, Mohamed T. Hammad, Hassan S. Hassan

    Published 2025-01-01
    “…Specifically, we utilize EfficientNetB3 and DenseNet121 pre-trained models in conjunction with the Co-Evolutionary Genetic Algorithm (CEGA) to classify brain tumors into four categories: gliomas, meningiomas, pituitary adenomas, and no tumors. …”
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    Article
  11. 1331

    Genetic variability of the fifth generation of nile tilapia Oreochromis niloticus using microsatellite DNA markers by Gloria Ika Satriani, Dinar Tri Soelistyowati, Dian Hardianto, Ratu Siti Aliah

    Published 2015-03-01
    “…The results showed that the amount of genetic variability on fifth generations of Nile tilapia from three strains was ranged between 33 to 100% and the highest genetic distance relationship between families was 0.3875. …”
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  12. 1332
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  14. 1334

    Determining optimum assembly zone for modular reconfigurable robots using multi-objective genetic algorithm by Ravikiran Pasumarthi, S. M. Bhagya P. Samarakoon, Mohan Rajesh Elara, Bing J. Sheu

    Published 2025-01-01
    “…The method uses a multi-objective Genetic Algorithm (GA) to minimize total travel distance and individual distance disparities. …”
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    Article
  15. 1335

    Genetic Instability Promotes the Acquisition of Chromosomal Imbalances in T1b and T1c Breast Adenocarcinomas by Harald Blegen, B. Michael Ghadimi, Annukka Jauho, Anders Zetterberg, Elina Eriksson, Gert Auer, Thomas Ried

    Published 2001-01-01
    “…In order to evaluate biological and genetic properties of early breast carcinomas we analyzed microdissected tissue from 33 primary breast carcinomas stage T1b and T1c with respect to the nuclear DNA content, the expression pattern of Ki‐67, cyclin A, p27KIP1, p53 and p21WAF1, and chromosomal gains and losses. …”
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  16. 1336

    Ataxia and Seizures despite Phenytoin: A Case Report Highlighting the Importance of TDM and Genetic Influences by Rachel Manoj, Arpita Meher, Jefry Winner G.

    Published 2024-01-01
    “…This case underscores the significance of TDM, genetic considerations in drug metabolism, and the need to be vigilant in treating epilepsy to prevent such adverse events.…”
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    Article
  17. 1337

    Bridging animal models and humans: neuroimaging as intermediate phenotypes linking genetic or stress factors to anhedonia by Huiling Guo, Yao Xiao, Shuai Dong, Jingyu Yang, Pengfei Zhao, Tongtong Zhao, Aoling Cai, Lili Tang, Juan Liu, Hui Wang, Ruifang Hua, Rongxun Liu, Yange Wei, Dandan Sun, Zhongchun Liu, Mingrui Xia, Yong He, Yankun Wu, Tianmei Si, Fay Y. Womer, Fuqiang Xu, Yanqing Tang, Jie Wang, Weixiong Zhang, Xizhe Zhang, Fei Wang

    Published 2025-01-01
    “…Abstract Background Intermediate phenotypes, such as characteristic neuroimaging patterns, offer unique insights into the genetic and stress-related underpinnings of neuropsychiatric disorders like depression. …”
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    Article
  18. 1338

    Comparison of the Genetic Alterations between Primary Colorectal Cancers and Their Corresponding Patient-Derived Xenograft Tissues by Sang Mi Yu, Seung-Hyun Jung, Yeun-Jun Chung

    Published 2018-06-01
    “…However, it is still unknown how much of the genetic alterations identified in primary tumors are consistently detected in tumor tissues in the PDX model. …”
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  19. 1339

    Prediction of energy consumption in four sectors using support vector regression optimized with genetic algorithm by Md. Sadikul Hasan, Md. Tarequzzaman, Md. Moznuzzaman, Md Abdul Ahad Juel

    Published 2025-01-01
    “…This paper unveils a genetic algorithm (GA)-optimized support vector regression (SVR) model designed to (i) predict electricity generation, (ii) predict energy consumption in four primary sectors—residential, industrial, commercial, and agricultural, and (iii) estimate sector-specific carbon emissions. …”
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  20. 1340