Article
Chemistry, Multidisciplinary
Bryan Queme, John C. Braisted, Patricia Dranchak, James Inglese
Summary: High throughput screening (HTS) is widely used in drug discovery and chemical biology to identify and characterize agents. Standard HTS data is usually represented as an x-y graph, while quantitative HTS (qHTS) data incorporates a third axis represented by concentration. qHTS data is challenging to display on a single graph due to the additional data points and logistic fit parameters.
JOURNAL OF CHEMINFORMATICS
(2023)
Article
Automation & Control Systems
T. Tony Cai, Rong Ma
Summary: This paper investigates the theoretical foundations of the t-SNE algorithm and presents a novel theoretical framework based on gradient descent. The paper analyzes the early exaggeration and embedding stages of t-SNE, explains their intrinsic mechanisms and empirical benefits, and provides theoretical guidance for applying t-SNE in various applications.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Biotechnology & Applied Microbiology
Ramyar Molania, Momeneh Foroutan, Johann A. Gagnon-Bartsch, Luke C. Gandolfo, Aryan Jain, Abhishek Sinha, Gavriel Olshansky, Alexander Dobrovic, Anthony T. Papenfuss, Terence P. Speed
Summary: Accurate identification and removal of unwanted variation in RNA-seq data are crucial for meaningful downstream analyses. Our PRPS strategy with RUV-III normalization effectively addresses this issue and can be applied to integrate and normalize large transcriptomic datasets from multiple sources.
NATURE BIOTECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Taiyun Kim, Owen Tang, Stephen T. Vernon, Katharine A. Kott, Yen Chin Koay, John Park, David E. James, Stuart M. Grieve, Terence P. Speed, Pengyi Yang, Gemma A. Figtree, John F. O'Sullivan, Jean Yee Hwa Yang
Summary: A new computational workflow is developed to remove unwanted data variation while preserving biologically relevant information in large scale metabolomics studies.
NATURE COMMUNICATIONS
(2021)
Article
Mathematical & Computational Biology
Yasser Aleman-Gomez, Ana Arribas-Gil, Manuel Desco, Antonio Elias, Juan Romo
Summary: Functional magnetic resonance imaging (fMRI) is a non-invasive technique that studies brain activity by measuring blood flow changes. We propose a novel visualization technique for high-dimensional functional brain imaging data, aiding in the identification of neuroscientific patterns.
STATISTICS IN MEDICINE
(2022)
Article
Biology
Tamasha Malepathirana, Damith Senanayake, Rajith Vidanaarachchi, Vini Gautam, Saman Halgamuge
Summary: This study investigates the ability of the dimensionality reduction method SONG to capture both discrete and continuous structures in biological data and compares the results with commonly used methods UMAP and PHATE. The findings show that SONG can preserve various patterns and performs better on datasets with both discrete and continuous structures. The quantitative evaluation validates the on par quality of SONG's low-dimensional embeddings compared to the other methods.
Article
Energy & Fuels
Mark A. Engle, Julien Chaput
Summary: Classical tools like cluster analysis and principal component analysis have been used for decades to understand complex geochemical data. However, recent developments in machine learning algorithms have shown that they can provide deeper insights than older methods. Combining Compositional Data Analysis (CoDA) with machine learning is an active area of research.
INTERNATIONAL JOURNAL OF COAL GEOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Caio Flexa, Walisson Gomes, Igor Moreira, Ronnie Alves, Claudomiro Sales
Summary: Dimensionality Reduction (DR) is important in understanding high-dimensional data, and the Polygonal Coordinate System (PCS) presented in this work offers an efficient geometric approach for this purpose. The study also introduces a new version of the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm using a PCS-based deterministic strategy, showcasing the efficiency of PCS in data embedding compared to other DR algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Sheng Feng, Liping Zhao, Haiyan Shi, Mengfei Wang, Shigen Shen, Weixing Wang
Summary: This article proposes a deep learning model for classifying high-dimensional data and aims to achieve optimal evaluation accuracy and robustness using multicriteria decision-making. A novel one-dimensional visual geometry group network (1D_VGGNet) is introduced to overcome the complexity and instability of high-dimensional data. Additionally, a one-dimensional convolutional neural network (1D_CNN) is used to effectively handle one-dimensional multicriteria decision-making.
APPLIED SOFT COMPUTING
(2023)
Article
Geriatrics & Gerontology
Samira A. Maboudian, Ming Hsu, Zhihao Zhang
Summary: This study introduces a method for analyzing verbal fluency data using recurrence analysis and proposes a new metric, DfD, to quantify semantic fluency data. The method is applied to compare Alzheimer's disease patients and healthy controls, showing significant differences in DfD between the two groups and complementing existing metrics in diagnostic prediction. Additionally, the visualization method allows for comparison of aggregate recall data at the group level.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Chemistry, Analytical
Mukesh Mishra, Gourab Sen Gupta, Xiang Gui
Summary: This paper investigates data compression methods for sensor nodes in wireless sensor networks. A hybrid method, combining run length encoding and adaptive Huffman encoding, is proposed for execution on the nodes. Simulations demonstrate the efficacy of the method in terms of energy efficiency, network speed, packet delivery rate, and residual energy.
Article
Chemistry, Multidisciplinary
Zhu-Jun Wang, Zhihua Liang, Xiao Kong, Xiaowen Zhang, Ruixi Qiao, Jinhuan Wang, Shuai Zhang, Zhiqun Zhang, Chaowu Xue, Guoliang Cui, Zhihong Zhang, Dingxin Zou, Zhi Liu, Qunyang Li, Wenya Wei, Xu Zhou, Zhilie Tang, Dapeng Yu, Enge Wang, Kaihui Liu, Feng Ding, Xiaozhi Xu
Summary: This study investigates the etching and growth of graphene in a two-dimensional confined space and reveals that the active bottom graphene layer can feed the growth of the top graphene layer with high efficiency, providing important insights for the design of high-efficiency catalysts.
Article
Geochemistry & Geophysics
Minghua Wang, Qiang Wang, Jocelyn Chanussot, Danfeng Hong
Summary: This study proposes a novel method to recover missing data in HORS images, combining total variation regularization and weighted tensor ring decomposition. The approach successfully restores missing content in HORS images while considering their inherent properties and structural information.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Biology
Federico Claudi, Adam L. Tyson, Luigi Petrucco, Troy W. Margrie, Ruben Portugues, Tiago Branco
Summary: The study introduces brainrender, an open-source Python package for interactive visualization of multidimensional datasets registered to brain atlases. This tool facilitates the creation of complex renderings with different data types in the same visualization, accelerating the analysis, interpretation, and dissemination of brain-wide multidimensional data.
Article
Energy & Fuels
Ying Yin, Zhiguo Qu, Chuanyong Zhu, Jianfei Zhang
Summary: Gas diffusion in nanoporous media is significantly lower compared to bulk systems due to the nanoconfinement effect, which increases with the average Knudsen number. A new concept called the confinement scope is introduced to quantify the magnitude of the nanoconfinement effect in predicting gas diffusivity in porous media. The proposed LED-LBM model successfully visualizes the spatial variations in local effective diffusivity and gas mass flux, revealing the influence of pore shape and Knudsen number on gas diffusion behavior.
Article
Immunology
Yannick O. Alexandre, Dominik Schienstock, Hyun Jae Lee, Luke C. Gandolfo, Cameron G. Williams, Sapna Devi, Bhupinder Pal, Joanna R. Groom, Wang Cao, Susan N. Christo, Claire L. Gordon, Graham Starkey, Rohit D'Costa, Laura K. Mackay, Ashraful Haque, Burkhard Ludewig, Gabrielle T. Belz, Scott N. Mueller
Summary: This article provides a comprehensive understanding of the cellular and molecular characteristics of fibroblastic stromal cells in the spleen, revealing their significance and diversity in maintaining tissue homeostasis and orchestrating immune responses.
SCIENCE IMMUNOLOGY
(2022)
Article
Immunology
Raissa Fonseca, Thomas N. Burn, Luke C. Gandolfo, Sapna Devi, Simone L. Park, Andreas Obers, Maximilien Evrard, Susan N. Christo, Frank A. Buquicchio, Caleb A. Lareau, Keely M. McDonald, Sarah K. Sandford, Natasha M. Zamudio, Nagela G. Zanluqui, Ali Zaid, Terence P. Speed, Ansuman T. Satpathy, Scott N. Mueller, Francis R. Carbone, Laura K. Mackay
Summary: Distinct programming of tissue residency in CD8(+) and CD4(+) T-RM cell subsets is regulated by the activity of transcription factor Runx3.
Article
Biotechnology & Applied Microbiology
Ramyar Molania, Momeneh Foroutan, Johann A. Gagnon-Bartsch, Luke C. Gandolfo, Aryan Jain, Abhishek Sinha, Gavriel Olshansky, Alexander Dobrovic, Anthony T. Papenfuss, Terence P. Speed
Summary: Accurate identification and removal of unwanted variation in RNA-seq data are crucial for meaningful downstream analyses. Our PRPS strategy with RUV-III normalization effectively addresses this issue and can be applied to integrate and normalize large transcriptomic datasets from multiple sources.
NATURE BIOTECHNOLOGY
(2022)
