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Journal articles on the topic 'Genomic techniques'

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1

Soni, Ravikant, Mohd Ashaq, P. Manjunath, et al. "Harnessing Genomic Resources and Molecular Breeding Techniques for Advancing Crop Resilience and Productivity." PLANT CELL BIOTECHNOLOGY AND MOLECULAR BIOLOGY 25, no. 11-12 (2024): 124–36. http://dx.doi.org/10.56557/pcbmb/2024/v25i11-128905.

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Crop improvement and adaptation are critical to ensure global food security in the face of climate change, population growth, and resource limitations. Exploiting genomic resources and molecular breeding techniques offers immense potential to accelerate the development of resilient, high-yielding crop varieties. This review provides an overview of the current state and future prospects of leveraging genomics and molecular breeding for crop improvement, with a focus on major food crops. We discuss key genomic resources such as reference genomes, transcriptomes, and pan-genomes, as well as power
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van Oppen, Madeleine J. H., and Melinda A. Coleman. "Advancing the protection of marine life through genomics." PLOS Biology 20, no. 10 (2022): e3001801. http://dx.doi.org/10.1371/journal.pbio.3001801.

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The rapid growth in genomic techniques provides the potential to transform how we protect, manage, and conserve marine life. Further, solutions to boost the resilience of marine species to climate change and other disturbances that characterize the Anthropocene require transformative approaches, made more effective if guided by genomic data. Although genetic techniques have been employed in marine conservation for decades and the availability of genomic data is rapidly expanding, widespread application still lags behind other data types. This Essay reviews how genetics and genomics have been u
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Xin-Yun Zhang, Fei Chen, Yuan-Ting Zhang, et al. "Signal processing techniques in genomic engineering." Proceedings of the IEEE 90, no. 12 (2002): 1822–33. http://dx.doi.org/10.1109/jproc.2002.805308.

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Dhaliwal, Neha. "Advanced Machine Learning Techniques to Improve Genomic Data Accuracy for Precision Medicine." International Journal of Science and Research (IJSR) 13, no. 6 (2024): 579–84. http://dx.doi.org/10.21275/sr24608014916.

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C., Sravani, Pavani P., Vybhavi G.Y., G. Ramesh, Ali Farman, and Venkareswara Reddy L. "Decoding the Human Genome: Machine Learning Techniques for DNA Sequencing Analysis." E3S Web of Conferences 430 (2023): 01067. http://dx.doi.org/10.1051/e3sconf/202343001067.

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The decoding of the human genome has been a landmark achievement in the field of genomics, generating vast amounts of DNA sequencing data that necessitate sophisticated analysis techniques. In recent years, machine learning has emerged as a powerful tool in unravelling the complexities of genomic data and expediting research discoveries. This article explores the integration of machine learning techniques in DNA sequencing analysis, elucidating their applications in genome assembly, variant calling, personalized medicine, and drug discovery. Additionally, it addresses the ethical consideration
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Remyamol, K. M., and Samuel Philip. "A Study on Deep Learning Architectures and Dimensionality Reduction Techniques on Gene Expression Data." Applied Science and Biotechnology Journal for Advanced Research 3, no. 3 (2024): 8–13. https://doi.org/10.5281/zenodo.11211521.

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Genomics, driven by the evolution of high-throughput sequencing and microarray technologies, has become one of the key inventions of cracking the secrets of complex biological systems. The deep learning architecture not only provides with a powerful tool to derive the hidden insights from the huge amount of genomic data, but also enables to mine meaningful information. In this study, we will examine the application of deep learning methods in the analysis of genomics data, specifically on dimensionality reduction and predictive modeling for binary phenotypes. We focus on the problems with the
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Upadhyay, Tejal, and Samir Patel. "Identifying Subtypes of Cancer Using Genomic Data by Applying Data Mining Techniques." International Journal of Natural Computing Research 8, no. 3 (2019): 55–64. http://dx.doi.org/10.4018/ijncr.2019070104.

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This article is about the study of genomics structures and identifying cancer types from it. It divides into six parts. The first part is about the introduction of cancer, types of cancers, how cancer arises, etc. The second part is about the genomic study and how cancer is related to that, which features are used for the study. The third part is about the software which the authors have used to study these genomic structures, which data sets are used, and what is the final output for this study. The fourth part shows the proposed algorithm for the study. The fifth part shows the data preproce
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Kyselová, Jitka, Ladislav Tichý, and Kateřina Jochová. "The role of molecular genetics in animal breeding: A minireview." Czech Journal of Animal Science 66, No. 4 (2021): 107–11. http://dx.doi.org/10.17221/251/2020-cjas.

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Current animal breeding approaches are strongly associated with the development of sophisticated molecular genetics methods and techniques. Worldwide expansion of genomic selection can be achieved by the identification of genetic DNA markers and implementation of the microarray (“chip”) technology. Further advancement was associated with next-generation sequencing methods, high-throughput genotyping platforms, targeted genome editing techniques, and studies of epigenetic mechanisms. The remarkable development of “omics” technologies, such as genomics, epigenomics, transcriptomics, proteomics a
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Oghenetega E. Imiruaye and Liasu Ogunkanmi. "Proteomic and Genomic Techniques in Medical Research: Applications in Cancer, Diagnostics, And Personalized Medicine." International Journal of Latest Technology in Engineering Management & Applied Science 14, no. 6 (2025): 959–67. https://doi.org/10.51583/ijltemas.2025.1406000106.

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Abstract: Advancements in proteomic and genomic technologies have transformed molecular biology by enabling comprehensive analysis of biological systems at the molecular level. This literature review explores the evolution, methodologies, and practical applications of key proteomic and genomic techniques. In proteomics, tools such as two-dimensional electrophoresis, mass spectrometry, Western blotting, Edman degradation, and functional protein microarrays have facilitated high-throughput protein identification, post-translational modification analysis, and biomarker discovery. Similarly, genom
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Yogi, Manas Kumar, and Yamuna Mundru. "Genomic Data Analysis with Variant of Secure Multi-Party Computation Technique." December 2023 5, no. 4 (2023): 450–70. http://dx.doi.org/10.36548/jtcsst.2023.4.006.

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The increasing availability of genomic data for research purposes necessitates innovative approaches to ensure privacy while facilitating collaborative analysis. This study explores the integration of a variant of Secure Multi-Party Computation (SMPC) techniques into genomic data analysis. The conventional challenges of sharing sensitive genetic information among multiple entities, such as research institutions or healthcare providers, are addressed by leveraging advanced cryptographic protocols. The research focuses on the development and implementation of a secure framework for collaborative
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Pérez-Ortín, José E., Daniel A. Medina, and Antonio Jordán-Pla. "Genomic Insights into the Different Layers of Gene Regulation in Yeast." Genetics Research International 2011 (November 22, 2011): 1–12. http://dx.doi.org/10.4061/2011/989303.

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The model organism Saccharomyces cerevisiae has allowed the development of new functional genomics techniques devoted to the study of transcription in all its stages. With these techniques, it has been possible to find interesting new mechanisms to control gene expression that act at different levels and for different gene sets apart from the known cis-trans regulation in the transcription initiation step. Here we discuss a method developed in our laboratory, Genomic Run-On, and other new methods that have recently appeared with distinct technical features. A comparison between the datasets ge
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SK, Bora. "Applications of Genomic Selection in Animal Breeding; Challenges and Opportunities." Open Access Journal of Microbiology & Biotechnology 8, no. 2 (2023): 1–7. http://dx.doi.org/10.23880/oajmb-16000263.

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The world's population demand and animal output are significantly out of balance. Although traditional breeding techniques have been successful in selecting animal populations for a variety of traits with economic significance, the reliability of breeding value has always been in doubt. According to simulation and experiment data, genomic selection for young animals without own performance can predict breeding values with good accuracy. Genetic markers that cover the entire genome are employed in genomic selection, a sort of marker-assisted selection, to ensure that all loci for quantitative t
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Saxena, Shivani. "Digital Signal Processing Approaches in the field of Genomics: A Recent Trend." Journal of Medical Science and clinical Research 12, no. 02 (2024): 66–77. http://dx.doi.org/10.18535/jmscr/v12i02.10.

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Digital signal processing (DSP) techniques have emerged as powerful tools in the field of genomics, enabling researchers to extract valuable insights from complex genetic data. This research paper presents a comprehensive analysis of the recent trends and advance- ments in applying DSP approaches to genomics. The objective is to provide an overview of the transformative role of DSP in genomic data analysis, variant calling, and interpretation. By leveraging DSP methods such as filtering, feature extraction, time-frequency analysis, and machine learning algorithms, researchers can enhance the q
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Vavekanand, Raja. "Data Security and Privacy in Genomics Research: A Comparative Analysis to Protect Confidentiality." Studies in Medical and Health Sciences 1, no. 1 (2024): 23–31. http://dx.doi.org/10.48185/smhs.v1i1.1158.

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The quick progress of genomics examination has driven a surge in the creation of significantly fragile genomic data, making ensuring its security essential. This data contains sensitive information roughly an individual's prosperity, family history, and defencelessness to ailments. Unauthorized access or mishandling can lead to isolation, stigmatization, and mystery breaches. The potential threats to genomic data affirmation are multifaceted, checking the chance of re-identification and extended defense lessness to data breaches, hacking events, and unauthorized get to by harmful actors. To ad
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Zajác Ševcová, Katarína. "Harmonizing EU Health Legislation for New Genomic Techniques." Novum Jus 18, no. 3 (2024): 95–125. https://doi.org/10.14718/novumjus.2024.18.3.4.

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This article examines the regulation and application of New Genomic Techniques (NGTs) and genetic testing within the European Union (EU). It scrutinises the detailed aspects of EU data protection laws, underscoring their significance in safeguarding patient privacy and facilitating data sharing in healthcare and research sectors. The paper delves into the ethical dimensions and technological advances in genetic engineering, specifically focusing on gene editing and direct-to-consumer genetic testing, illuminating the complex interplay between technology, ethics, and legal frameworks. The analy
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Aziz, Md Momin Al, Md Nazmus Sadat, Dima Alhadidi, et al. "Privacy-preserving techniques of genomic data—a survey." Briefings in Bioinformatics 20, no. 3 (2017): 887–95. http://dx.doi.org/10.1093/bib/bbx139.

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Nusrat, S., T. Harbig, and N. Gehlenborg. "Tasks, Techniques, and Tools for Genomic Data Visualization." Computer Graphics Forum 38, no. 3 (2019): 781–805. http://dx.doi.org/10.1111/cgf.13727.

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Swales, A. K. E., and N. Spears. "Genomic imprinting and reproduction." Reproduction 130, no. 4 (2005): 389–99. http://dx.doi.org/10.1530/rep.1.00395.

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Genomic imprinting is the parent-of-origin specific gene expression which is a vital mechanism through both development and adult life. One of the key elements of the imprinting mechanism is DNA methylation, controlled by DNA methyltransferase enzymes. Germ cells undergo reprogramming to ensure that sex-specific genomic imprinting is initiated, thus allowing normal embryo development to progress after fertilisation. In some cases, errors in genomic imprinting are embryo lethal while in others they lead to developmental disorders and disease. Recent studies have suggested a link between the use
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Ullah, Kaleem, and Abdul Waheed. "Review: Genetic Improvement in Livestock: A Journey from Conventional Breeding to Genomic Precision." Veterinary Biomedical and Clinical Journal 7, no. 1 (2025): 30–44. https://doi.org/10.21776/ub.vetbioclinj.2025.007.01.3.

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From conventional breeding techniques to the advent of genomic precision, the practice of genetically altering livestock has experienced a substantial change over the last century. Conventional breeding methods like selective breeding, crossbreeding and artificial insemination (AI) have long served as the foundation for livestock development. Even though these techniques were successful, they were unable to fully address complex genetic factors as such techniques were primarily reliant on phenotypic selection and observable traits. Although early crossbreeding innovations aimed to enhance perf
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Morrison, Carl. "Fluorescent In Situ Hybridization and Array Comparative Genomic Hybridization: Complementary Techniques for Genomic Evaluation." Archives of Pathology & Laboratory Medicine 130, no. 7 (2006): 967–74. http://dx.doi.org/10.5858/2006-130-967-fishaa.

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Abstract During the past few years a new high-throughput molecular technology, array comparative genomic hybridization, has received a great deal of attention. As a DNA-based tool, this technique is presumably more reproducible than expression arrays. In this review, I discuss how array comparative genomic hybridization is remarkably similar with regard to genome analysis to fluorescent in situ hybridization, a technique that is generally regarded as one of the more accurate and reproducible molecular techniques in diagnostic surgical pathology. A thorough understanding of this technology will
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Niu, Dongsheng, Qing Zhao, Linbo Xu, and Kejian Lin. "Physiological and Molecular Mechanisms of Lepidopteran Insects: Genomic Insights and Applications of Genome Editing for Future Research." International Journal of Molecular Sciences 25, no. 22 (2024): 12360. http://dx.doi.org/10.3390/ijms252212360.

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Lepidopteran insects are a major threat to global agriculture, causing significant crop losses and economic damage. Traditional pest control methods are becoming less effective due to the rapid evolution of insecticide resistance. This study explores the current status and genomic characteristics of 1315 Lepidopteran records, alongside an overview of relevant research, utilizing advanced functional genomics techniques, including RNA-seq and CRISPR/Cas9 gene-editing technologies to uncover the molecular mechanisms underlying insecticide resistance. Our genomic analysis revealed significant vari
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Yue, Tianwei, Yuanxin Wang, Longxiang Zhang, et al. "Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models." International Journal of Molecular Sciences 24, no. 21 (2023): 15858. http://dx.doi.org/10.3390/ijms242115858.

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The data explosion driven by advancements in genomic research, such as high-throughput sequencing techniques, is constantly challenging conventional methods used in genomics. In parallel with the urgent demand for robust algorithms, deep learning has succeeded in various fields such as vision, speech, and text processing. Yet genomics entails unique challenges to deep learning, since we expect a superhuman intelligence that explores beyond our knowledge to interpret the genome from deep learning. A powerful deep learning model should rely on the insightful utilization of task-specific knowledg
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Chaudhary, Neeraj, Romesh Kumar Salgotra, and Bhagirath Singh Chauhan. "Genetic Enhancement of Cereals Using Genomic Resources for Nutritional Food Security." Genes 14, no. 9 (2023): 1770. http://dx.doi.org/10.3390/genes14091770.

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Advances in genomics resources have facilitated the evolution of cereal crops with enhanced yield, improved nutritional values, and heightened resistance to various biotic and abiotic stresses. Genomic approaches present a promising avenue for the development of high-yielding varieties, thereby ensuring food and nutritional security. Significant improvements have been made within the omics domain, specifically in genomics, transcriptomics, and proteomics. The advent of Next-Generation Sequencing (NGS) techniques has yielded an immense volume of data, accompanied by substantial progress in bioi
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Gutiérrez, Abel F., and Patricia Mollinedo Portugal. "Estudio genómico de la Quinua (Chenopodium quinoa Willd): Técnicas de secuenciación e identificación genómica. Una revision." REVISTA CON-CIENCIA 10, no. 1 (2022): 67–84. http://dx.doi.org/10.53287/owrp5412ir44z.

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Introducción. La quinua (Chenopodium quinoa Willd), es considerado uno de los alimentos más completos debido a su alto contenido en ácidos grasos, oligoelementos y proteínas ricas en aminoácidos esenciales; sin embargo, también posee metabolitos con propiedades anti nutricionales (saponinas) que deben ser eliminados antes de su consumo. Algunos estudios realizados en el genoma de la quinua, se han basado en la identificación de genes involucrados en la producción de saponinas para inhibir su expresión y evitar los tratamientos de pos cosecha (escarificado). Objetivo. Establecer, mediante revis
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Miedaner, Thomas, Ana Luisa Galiano-Carneiro Boeven, David Sewodor Gaikpa, Maria Belén Kistner, and Cathérine Pauline Grote. "Genomics-Assisted Breeding for Quantitative Disease Resistances in Small-Grain Cereals and Maize." International Journal of Molecular Sciences 21, no. 24 (2020): 9717. http://dx.doi.org/10.3390/ijms21249717.

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Generating genomics-driven knowledge opens a way to accelerate the resistance breeding process by family or population mapping and genomic selection. Important prerequisites are large populations that are genomically analyzed by medium- to high-density marker arrays and extensive phenotyping across locations and years of the same populations. The latter is important to train a genomic model that is used to predict genomic estimated breeding values of phenotypically untested genotypes. After reviewing the specific features of quantitative resistances and the basic genomic techniques, the possib
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Sabatello, Maya, and Paul S. Appelbaum. "Raising Genomic Citizens: Adolescents and the Return of Secondary Genomic Findings." Journal of Law, Medicine & Ethics 44, no. 2 (2016): 292–308. http://dx.doi.org/10.1177/1073110516654123.

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Whole genome and exome sequencing (WGS/WES) techniques raise hope for a new scale of diagnosis, prevention, and prediction of genetic conditions, and improved care for children. For these hopes to materialize, extensive genomic research with children will be needed. However, the use of WGS/WES in pediatric research settings raises considerable challenges for families, researchers, and policy development. In particular, the possibility that these techniques will generate genetic findings unrelated to the primary goal of sequencing has stirred intense debate about whether, which, how, and when t
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Banka, Vaishnavi, Reginah Pheirim, and Prajyot Waghmode. "Genomic Innovations in Wheat (Triticum aestivum L.): A Comprehensive Review of Recent Developments and Future Directions." Journal of Advances in Biology & Biotechnology 27, no. 9 (2024): 795–806. http://dx.doi.org/10.9734/jabb/2024/v27i91353.

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Genomic innovations have revolutionized the field of wheat breeding by providing advanced tools to enhance its biofortification and overall productivity. This comprehensive review synthesizes recent developments in wheat genomics, focusing on the integration of various approaches such as genome-wide association studies (GWAS), marker-assisted selection (MAS), and quantitative trait locus (QTL) mapping. These genomic techniques have significantly advanced our understanding of the genetic basis underlying key traits, facilitating the development of wheat varieties with improved nutritional profi
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Marçais, Guillaume, Brad Solomon, Rob Patro, and Carl Kingsford. "Sketching and Sublinear Data Structures in Genomics." Annual Review of Biomedical Data Science 2, no. 1 (2019): 93–118. http://dx.doi.org/10.1146/annurev-biodatasci-072018-021156.

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Large-scale genomics demands computational methods that scale sublinearly with the growth of data. We review several data structures and sketching techniques that have been used in genomic analysis methods. Specifically, we focus on four key ideas that take different approaches to achieve sublinear space usage and processing time: compressed full-text indices, approximate membership query data structures, locality-sensitive hashing, and minimizers schemes. We describe these techniques at a high level and give several representative applications of each.
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Sunagar, Ramesh, and Manoj Kumar Pandey. "Genomic Approaches for Enhancing Yield and Quality Traits in Mustard (Brassica spp.): A Review of Breeding Strategies." Journal of Advances in Biology & Biotechnology 27, no. 6 (2024): 174–85. http://dx.doi.org/10.9734/jabb/2024/v27i6877.

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Mustard, a vital oilseed crop, plays a significant role in global agriculture due to its versatile applications in food, feed, and biofuel industries. However, meeting the increasing demands for yield and quality traits poses a substantial challenge to mustard breeders. In response, genomic approaches have emerged as powerful tools to expedite mustard breeding programs by unraveling the genetic basis of key agronomic traits. This review provides a comprehensive overview of genomic strategies aimed at enhancing yield and quality traits in mustard. Beginning with an exploration of traditional br
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Monaco, Alfonso, Ester Pantaleo, Nicola Amoroso, et al. "A primer on machine learning techniques for genomic applications." Computational and Structural Biotechnology Journal 19 (2021): 4345–59. http://dx.doi.org/10.1016/j.csbj.2021.07.021.

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Ceciliani, F., P. Roccabianca, C. Giudice, and C. Lecchi. "Application of post-genomic techniques in dog cancer research." Molecular BioSystems 12, no. 9 (2016): 2665–79. http://dx.doi.org/10.1039/c6mb00227g.

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We present in this review the most recent achievement in the application of transcriptomics, proteomics and metabolomics to canine cancer research. The protocols to recover material suitable for omics analyses from formalin-fixed, paraffin-embedded tissues are highlighted, together with the potential of omics in veterinary cancer diagnostics.
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Bhattacherjee, Sanmitro, Susmita Mukherjee, Asmita Podder, and Sonali Paul. "Culmination of molecular genomic techniques in forensic crime investigation." Forensic Science International 366 (January 2025): 112302. http://dx.doi.org/10.1016/j.forsciint.2024.112302.

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Ricroch, A., and C. Miscopein. "Biotechnologies and new genomic techniques for ornamental plant breeding." Acta Horticulturae, no. 1417 (January 2025): 1–12. https://doi.org/10.17660/actahortic.2025.1417.1.

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Torres-Corral, Yolanda, and Ysabel Santos. "Identification and typing ofVagococcus salmoninarumusing genomic and proteomic techniques." Journal of Fish Diseases 42, no. 4 (2019): 597–612. http://dx.doi.org/10.1111/jfd.12967.

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Gazalle, Paula Furtado, Diago Dutra Lima, Kauê Rodriguez Martins, and Rodrigo Casquero Cunha. "PCR AND OTHER GENOMIC TECHNIQUES APPLIED TO VETERINARY MEDICINE." REVISTA FOCO 16, no. 3 (2023): e1226. http://dx.doi.org/10.54751/revistafoco.v16n3-010.

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The detection of specific DNA sequences by Polymerase Chain Reaction (PCR) has been proven extremely valuable for genetic analysis and diagnosis of a variety of infectious disease pathogens in the veterinary sciences. Genomic techniques applied to veterinary medicine has become fundamental, whether for the detection of pathogens through the use of PCR and its variations or by other techniques that allow the creation and development of recombinant proteins and vaccines for veterinary use. PCR technology has become an indispensable tool in veterinary diagnosis. Other techniques, which play an im
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Dąbrowska, Joanna, Jacek Sroka, and Tomasz Cencek. "Investigating Cryptosporidium spp. Using Genomic, Proteomic and Transcriptomic Techniques: Current Progress and Future Directions." International Journal of Molecular Sciences 24, no. 16 (2023): 12867. http://dx.doi.org/10.3390/ijms241612867.

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Cryptosporidiosis is a widespread disease caused by the parasitic protozoan Cryptosporidium spp., which infects various vertebrate species, including humans. Once unknown as a gastroenteritis-causing agent, Cryptosporidium spp. is now recognized as a pathogen causing life-threatening disease, especially in immunocompromised individuals such as AIDS patients. Advances in diagnostic methods and increased awareness have led to a significant shift in the perception of Cryptosporidium spp. as a pathogen. Currently, genomic and proteomic studies play a main role in understanding the molecular biolog
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Waldispuhl, Jerome, and Mathieu Blanchette. "Phylo and Open-Phylo: A Human-Computing Platform for Comparative Genomics." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (September 5, 2014): 73–74. http://dx.doi.org/10.1609/hcomp.v2i1.13137.

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Comparative genomics is a field of research that aims to provide us accurate mappings between the genetic material of multiple species. These techniques are useful for biomedical research and evolutionary studies. We present Phylo and Open-Phylo, an open citizen science platform and human computing-game for comparative genomic studies that reached more than 300,000 users.
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Sulaiman, Irshad M., Lihua Xiao, and Altaf A. Lal. "Evaluation of Cryptosporidium parvumGenotyping Techniques." Applied and Environmental Microbiology 65, no. 10 (1999): 4431–35. http://dx.doi.org/10.1128/aem.65.10.4431-4435.1999.

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ABSTRACT We evaluated the specificity and sensitivity of 11 previously described species differentiation and genotyping PCR protocols for detection of Cryptosporidium parasites. Genomic DNA from three species of Cryptosporidium parasites (genotype 1 and genotype 2 of C. parvum, C. muris, and C. serpentis), two Eimeria species (E. neischulzi and E. papillata), and Giardia duodenalis were used to evaluate the specificity of primers. Furthermore, the sensitivity of the genotyping primers was tested by using genomic DNA isolated from known numbers of oocysts obtained from a genotype 2 C. parvum is
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kartheek, J. Pavan. "Predicting Fetal Features from DNA Through Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem41160.

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Predicting fetal features from DNA using machine learning represents a pioneering advancement in prenatal diagnostics and personalized medicine. This research leverages genomic data and advanced machine learning techniques to predict fetal traits, such as physical attributes and potential health conditions, with high precision. By integrating feature selection methods and predictive modeling, the study highlights the potential of machine learning in enabling early diagnosis and personalized healthcare planning. Ethical considerations, including data privacy and responsible use of genetic infor
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Gilbertson, Marie L. J., Nicholas M. Fountain-Jones, and Meggan E. Craft. "Incorporating genomic methods into contact networks to reveal new insights into animal behaviour and infectious disease dynamics." Behaviour 155, no. 7-9 (2018): 759–91. http://dx.doi.org/10.1163/1568539x-00003471.

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Abstract Utilization of contact networks has provided opportunities for assessing the dynamic interplay between pathogen transmission and host behaviour. Genomic techniques have, in their own right, provided new insight into complex questions in disease ecology, and the increasing accessibility of genomic approaches means more researchers may seek out these tools. The integration of network and genomic approaches provides opportunities to examine the interaction between behaviour and pathogen transmission in new ways and with greater resolution. While a number of studies have begun to incorpor
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T Murali Krishn. "Improving Genomic Analysis with Convolutional, Recurrent, and Transformer Neural Networks." Power System Technology 48, no. 3 (2024): 764–80. https://doi.org/10.52783/pst.874.

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The advent of deep learning has revolutionized the field of genomics, offering new ways to analyze and interpret complex genetic data. This paper introduces GenomicNet, a novel deep learning-based system designed to advance genomic analysis through a unified framework. GenomicNet integrates convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer architectures to predict the effects of genetic variants, identify regulatory elements, and model protein structures with high accuracy. Comparative evaluations show that GenomicNet outperforms existing systems like Deep
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Saha, Sajal, Deepa Bhadana, Rinkey Arya, Pankaj Kumar Shah, Nishtha, and Pravesh Kumar. "An Overview of Bioinformatics and Computational Genomics in Modern Plant Science." International Journal of Environment and Climate Change 13, no. 9 (2023): 1530–44. http://dx.doi.org/10.9734/ijecc/2023/v13i92385.

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Bioinformatics plays monumental role in decoding the genomic landscape of plant species for agricultural advancements. While only a few plant genomes have been fully sequenced, the pan-genomic approach, involving the study of both the core and accessory genomes, is necessary to fully understand a species' genomic content. Bioinformatics, at the intersection of computer science and biology, handles the vast biological data generated during plant genomics research, facilitating data analysis, organization, and interpretation. By developing algorithms and tools, bioinformatics aids in gene predic
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Wang, Mingcheng, Rui Li, and Qi Zhao. "Multi-Omics Techniques in Genetic Studies and Breeding of Forest Plants." Forests 14, no. 6 (2023): 1196. http://dx.doi.org/10.3390/f14061196.

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In recent years, the ecological and economic values of forest plants have been gradually recognized worldwide. However, the growing global demand for new forest plant varieties with higher wood production capacity and better stress tolerance cannot be satisfied by conventional phenotype-based breeding, marker-assisted selection, and genomic selection. In the recent past, diverse omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics, have been developed rapidly, providing powerful tools for the precision genetic breeding of forest plants. Genomics la
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S., M. Shifana Rayesha, Banu Aisha, Rahman Afzalur, and Priya Sharon. "Unveiling DNA sequences: a comparison of machine learning and deep learning techniques for prediction." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 4 (2024): 4583–93. https://doi.org/10.11591/ijai.v13.i4.pp4583-4593.

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DNA is the biological macromolecule unit that carries the information of all protein, amino acid sequences. With the help of this protein sequence, we explore the mutated gene and disease-causing mutated genomic pattern. Currently, the progression of genomic innovation is the source of DNA arrangement information developing at a dangerous rate—external factors have stimulated the volume of research into DNA genomes. Initially, the development process of DNA sequencing is accomplished with the support of the Database, data structures, and sequence similarity. The method is capable of extr
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Turzynski, Victoria, Indra Monsees, Cristina Moraru, and Alexander J. Probst. "Imaging Techniques for Detecting Prokaryotic Viruses in Environmental Samples." Viruses 13, no. 11 (2021): 2126. http://dx.doi.org/10.3390/v13112126.

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Viruses are the most abundant biological entities on Earth with an estimate of 1031 viral particles across all ecosystems. Prokaryotic viruses—bacteriophages and archaeal viruses—influence global biogeochemical cycles by shaping microbial communities through predation, through the effect of horizontal gene transfer on the host genome evolution, and through manipulating the host cellular metabolism. Imaging techniques have played an important role in understanding the biology and lifestyle of prokaryotic viruses. Specifically, structure-resolving microscopy methods, for example, transmission el
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Airlangga, Gregorius. "Application of Traditional Machine Learning Techniques for the Classification of Human DNA Sequences: A Comparative Study of Random Forest and XGBoost." Jurnal Informatika Universitas Pamulang 9, no. 1 (2024): 23–30. https://doi.org/10.32493/informatika.v9i1.39353.

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This study evaluates the performance of hybrid machine learning models, specifically Random Forest and XGBoost, in classifying human DNA sequences into seven functional classes. Utilizing advanced feature vectorization techniques, this research addresses the challenges of analyzing high-dimensional genomic data. Both models were trained and tested on a dataset of annotated human DNA sequences, with an emphasis on generalizability to new, unseen data. Our results indicate that the Random Forest model achieved an accuracy of 87.98%, slightly outperforming the XGBoost model, which recorded an acc
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Aupperle-Lellbach, Heike, Alexandra Kehl, Simone de Brot, and Louise van der Weyden. "Clinical Use of Molecular Biomarkers in Canine and Feline Oncology: Current and Future." Veterinary Sciences 11, no. 5 (2024): 199. http://dx.doi.org/10.3390/vetsci11050199.

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Molecular biomarkers are central to personalised medicine for human cancer patients. It is gaining traction as part of standard veterinary clinical practice for dogs and cats with cancer. Molecular biomarkers can be somatic or germline genomic alterations and can be ascertained from tissues or body fluids using various techniques. This review discusses how these genomic alterations can be determined and the findings used in clinical settings as diagnostic, prognostic, predictive, and screening biomarkers. We showcase the somatic and germline genomic alterations currently available to date for
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Damaj, Mona B., Phillip D. Beremand, Marco T. Buenrostro-Nava, et al. "Isolating promoters of multigene family members from the polyploid sugarcane genome by PCR-based walking in BAC DNA." Genome 53, no. 10 (2010): 840–47. http://dx.doi.org/10.1139/g10-064.

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The availability of a wider range of promoters for regulated expression in valuable transgenic crops would benefit functional genomics studies and current biotechnology programs aimed at improved productivity. Polymerase chain reaction (PCR)-based genome walking techniques are commonly used to isolate promoters or 5′ flanking genomic regions adjacent to known cDNA sequences in genomes that are not yet completely sequenced. However, these techniques are problematic when applied directly to DNA isolated from crops with highly complex and large genomes. An adaptor ligation-mediated PCR-based BAC
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M, Gidi. "Advances in Genomics: Crops Adapting to Climate Change." Open Access Journal of Microbiology & Biotechnology 8, no. 2 (2023): 1–8. http://dx.doi.org/10.23880/oajmb-16000264.

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In a world where food consumption is rising, climate change poses a severe danger to feeding a growing population. Previously, increased agricultural output was achieved by using fertilizer and insecticides for improved weed and pest control. However, these techniques rely on exhaustible resources and are frequently unstable. Current developments in advanced genetics are paving the door for long-term agricultural intensification and greater global warming crop adaptability. The amount of quality genomic information accessible has been rapidly increasing as a result of the widespread usage of g
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Singh, Nidhi, Rahul Singh Raghuvanshi, Rajul Soni, Somil Singh Chauhan, and Teena Patidar. "Genomic advancements of millets: a miracle crop." Ecology, Environment and Conservation 31, no. 01 (2025): 378–84. https://doi.org/10.53550/eec.2025.v31i01.068.

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Millets is a nutri-cereal, poor man’s crop blessed with unlimited miracle with multi-dimensional application to meet food security, nutrition security, livelihood security, and also the environmental security. Along with supplementing nutritional diet it is important as climate resilient crop. India is largest producer of millets in world and 5th largest exporter in the world. Thus, the robust features, less water requirement and ecological benefits associated with these crops have made millets a ideal crop for cultivation. In addition to the agronomical, physiological attributes biochemical
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