Review
Chemistry, Analytical
Gabrielle Kosoy, Benjamin L. Miller
Summary: Arrayed imaging reflectometry (AIR) is a thin-film interference sensor technique that can be used for detecting various biomolecules and pathogens, and it has high sensitivity and multiplex capability.
Article
Biochemical Research Methods
Stefano Grasso, Valentina Dabene, Margriet M. W. B. Hendriks, Priscilla Zwartjens, Rene Pellaux, Martin Held, Sven Panke, Jan Maarten van Dijl, Andreas Meyer, Tjeerd van Rij
Summary: The passage of proteins across biological membranes via the Sec pathway is a universally conserved process with critical functions. Estimating the impact of physicochemical signal peptide features on protein secretion levels was achieved through a high-throughput assay and machine learning model. The results allow for quantifying feature importance and predicting protein secretion levels, providing a versatile tool for signal peptide design and evaluation.
ACS SYNTHETIC BIOLOGY
(2023)
Article
Biochemical Research Methods
Yang Chen, Shue Chen, Elissa P. Lei
Summary: This study presents a novel differential analysis method (DiffChIPL) based on Limma, which accurately detects differential peaks in ChIP-seq data. The method shows superior performance in simulations and real datasets, and exhibits better differential analysis capability in various applications.
Article
Biochemistry & Molecular Biology
Brittany Cain, Jordan Webb, Zhenyu Yuan, David Cheung, Hee-Woong Lim, Rhett A. Kovall, Matthew T. Weirauch, Brian Gebelein
Summary: Homeodomain proteins can form cooperative homodimer complexes on DNA sites with precise spacing requirements, with approximately one third of the paired-like homeodomain proteins binding to palindromic sequences spaced 3 bp apart. Other homeodomain proteins bind to sites with distinct orientation and spacing requirements. Computational analysis using structural models and computational mining of HT-SELEX data allowed the identification of key amino acid differences that differentiate between cooperative and non-cooperative factors. In vivo validation using available genomic data confirmed the predicted cooperative dimer sites for a subset of factors.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Plant Sciences
Alper Adak, Myeongjong Kang, Steven L. Anderson, Seth C. Murray, Diego Jarquin, Raymond K. W. Wong, Matthias Katzfuss
Summary: High-throughput phenotyping (HTP) has not resulted in many new biological discoveries, but field-based HTP (FHTP) using UAVs has the potential to monitor plant population interactions with the environment. This study collected phenotypic data on maize lines in different environments and predicted complex traits using genomic and phenomic data. The study revealed a time-dependent association between genotypes and abiotic stresses, highlighting the importance of temporal phenomic data.
JOURNAL OF EXPERIMENTAL BOTANY
(2023)
Article
Materials Science, Multidisciplinary
Yonggang Yan, Zongrui Pei, Michael C. Gao, Scott Misture, Kun Wang
Summary: The interest in high entropy ceramics (HECs) has steadily increased due to their superior properties. Using a data-driven approach, a rational rule for designing single-phase high entropy transition metal diborides (HEBs) is discovered. The machine learning (ML) model trained on data collected via high-throughput experiments (HTEs) achieves an experimental validation accuracy of 93.75% with the K nearest neighbors (KNN) model. The empirical rule proposed indicates that HEBs tend to form a single phase when delta B_TM < 3.66 and multiphase otherwise, with a high accuracy of 93.33% for new HEBs predictions. Additionally, 165 high quality HEBs data are contributed, promoting the development of materials informatics in HEBs and accelerating the search for new HECs.
Article
Chemistry, Medicinal
Yuanqing Tang, Zhi Li, Mansoor Ani Najeeb Nellikkal, Hamed Eramian, Emory M. Chan, Alexander J. Norquist, D. Frank Hsu, Joshua Schrier
Summary: Combinatorial fusion analysis (CFA) is an effective approach for combining multiple scoring systems to improve prediction quality and address data quality issues. By combining diverse machine learning models, better prediction results can be achieved.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Agriculture, Dairy & Animal Science
Yuhua Fu, Pengyu Fan, Lu Wang, Ziqiang Shu, Shilin Zhu, Siyuan Feng, Xinyun Li, Xiaotian Qiu, Shuhong Zhao, Xiaolei Liu
Summary: This study utilized massive public data to improve the annotation of known miRNAs, identify a large number of novel miRNAs, and predict target genes for all pig miRNAs. The correlation-based strategy provided a new perspective for predicting target genes of miRNAs, offering additional evidence of expression compared with traditional methods, and is applicable to other nonmodel organisms with incomplete annotation information.
JOURNAL OF ANIMAL SCIENCE
(2021)
Review
Pharmacology & Pharmacy
Charles Hadley S. King, Jonathon Keeney, Nuria Guimera, Souvik Das, Michiel Weber, Brian Fochtman, Mark O. Walderhaug, Sneh Talwar, Janisha A. Patel, Raja Mazumder, Eric F. Donaldson
Summary: This project demonstrates the use of the IEEE 2791-2020 Standard (BioCompute Objects [BCO]) to enable clear communication of NGS analysis results. It replicates a clinical trial and performs two independent analyses to validate the consistency of the results, showcasing how a template BCO enhances confidence in the regulatory submission process.
DRUG DISCOVERY TODAY
(2022)
Article
Chemistry, Analytical
Haixu Yang, Jiahui Yu, Luhong Jin, Yunpeng Zhao, Qi Gao, Changrong Shi, Lei Ye, Dong Li, Hai Yu, Yingke Xu
Summary: Droplet digital PCR (ddPCR) is a technique for quantifying nucleic acid molecules, and accurate recognition of positive droplets in ddPCR images is crucial for accurate analysis. In this study, we developed a deep learning-based ddPCR droplet detection framework that can achieve high-precision localization and classification of droplets under different illumination conditions, improving the accuracy and robustness of analysis.
Article
Biochemical Research Methods
Benedek Bozoky, Laszlo Szekely, Ingemar Ernberg, Andrii Savchenko
Summary: The human protein atlas (HPA) is a valuable online database that provides image-based protein expression data in normal and cancerous tissues. To enhance the usability of the database, researchers have developed the AtlasGrabber software, which facilitates large-scale screening and analysis of the images. This software has been used to identify new markers for prostate cancer diagnostics.
BMC BIOINFORMATICS
(2022)
Article
Chemistry, Physical
Tianle Yue, Jinlong He, Lei Tao, Ying Li
Summary: The ability to store and release elastic strain energy, as well as mechanical strength, are crucial factors in mechanical systems. To improve the resilience of linear elastic solids, a computational method using machine learning is proposed to identify polymers with high modulus of resilience. This method efficiently speeds up the discovery of high-performing polymers and can be applied to other polymer material discovery challenges.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Multidisciplinary
George I. Lambrou, Kleanthis Vichos, Dimitrios Koutsouris, Apostolos Zaravinos
Summary: Urinary bladder cancer (UBC) is the second most common urogenital solid tumor, with several new candidate prognostic markers identified. This study aimed to detect global gene co-expression profiles among a high number of UBC tumors, resulting in the identification of novel candidate markers and potential drugs for the disease.
APPLIED SCIENCES-BASEL
(2021)
Review
Chemistry, Analytical
Lina Shi, Sutong Liu, Xue Li, Xiwei Huang, Hongzhi Luo, Qianwen Bai, Zhu Li, Lijun Wang, Xiaoxin Du, Cheng Jiang, Shan Liu, Chenzhong Li
Summary: High-throughput screening platforms are crucial for processing large amounts of experimental data rapidly and efficiently. The development of miniaturized high-throughput screening platforms is essential in the fields of biotechnology, medicine, and pharmacology. Droplet microarrays, as novel screening platforms, can effectively overcome the disadvantages of traditional microtiter plates, such as high reagent and cell consumption, low throughput, and cross-contamination. This article provides a brief overview of the preparation and compound addition methods of droplet microarrays, as well as their applications in biomedicine, drug development, and individualized medicine.
Article
Plant Sciences
Lixin Cheng, Yonglun Zeng, Shuai Hu, Ning Zhang, Kenneth C. P. Cheung, Baiying Li, Kwong-Sak Leung, Liwen Jiang
Summary: This study identified autophagy-related modules in Arabidopsis using a systems-level algorithm, revealing that newly identified genes in these modules are upregulated and coexpressed during senescence. Additionally, the Golgi apparatus autophagy-related module, ARM13, was found to function in the autophagy process through module clustering and functional analysis.