A review on advancements in feature selection and feature extraction for high-dimensional NGS data analysis

Borah, Kasmika; Das, Himanish Shekhar; Seth, Soumita; Mallick, Koushik; Rahaman, Zubair; Mallik, Saurav

doi:10.1007/s10142-024-01415-x

Cited by 4 publications

References 175 publications

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An overview on olfaction in the biological, analytical, computational, and machine learning fields

Chiera,

Costa,

Alcaro

et al. 2024

Archiv der Pharmazie

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Recently, the comprehension of odor perception has advanced, unveiling the mysteries of the molecular receptors within the nasal passages and the intricate mechanisms governing signal transmission between these receptors, the olfactory bulb, and the brain. This review provides a comprehensive panorama of odors, encompassing various topics ranging from the structural and molecular underpinnings of odorous substances to the physiological intricacies of olfactory perception. It extends to elucidate the analytical methods used for their identification and explores the frontiers of computational methodologies.

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An overview on olfaction in the biological, analytical, computational, and machine learning fields

Chiera,

Costa,

Alcaro

et al. 2024

Archiv der Pharmazie

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Addressing Wide-Data Studies of Gene Expression Microarrays with the Relevance Feature and Vector Machine

Belenguer-Llorens,

Sevilla salcedo,

Parrado Hernández

et al. 2024

Preprint

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Techniques for Canopy to Organ Level Plant Feature Extraction via Remote and Proximal Sensing: A Survey and Experiments

Nethala,

Um,

Vemula

et al. 2024

Remote Sensing

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This paper presents an extensive review of techniques for plant feature extraction and segmentation, addressing the growing need for efficient plant phenotyping, which is increasingly recognized as a critical application for remote sensing in agriculture. As understanding and quantifying plant structures become essential for advancing precision agriculture and crop management, this survey explores a range of methodologies, both traditional and cutting-edge, for extracting features from plant images and point cloud data, as well as segmenting plant organs. The importance of accurate plant phenotyping in remote sensing is underscored, given its role in improving crop monitoring, yield prediction, and stress detection. The review highlights the challenges posed by complex plant morphologies and data noise, evaluating the performance of various techniques and emphasizing their strengths and limitations. The insights from this survey offer valuable guidance for researchers and practitioners in plant phenotyping, advancing the fields of plant science and agriculture. The experimental section focuses on three key tasks: 3D point cloud generation, 2D image-based feature extraction, and 3D shape classification, feature extraction, and segmentation. Comparative results are presented using collected plant data and several publicly available datasets, along with insightful observations and inspiring directions for future research.

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A review on advancements in feature selection and feature extraction for high-dimensional NGS data analysis

Cited by 4 publications

References 175 publications

An overview on olfaction in the biological, analytical, computational, and machine learning fields

An overview on olfaction in the biological, analytical, computational, and machine learning fields

Addressing Wide-Data Studies of Gene Expression Microarrays with the Relevance Feature and Vector Machine

Techniques for Canopy to Organ Level Plant Feature Extraction via Remote and Proximal Sensing: A Survey and Experiments

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