Article
Biochemical Research Methods
Lin Wang, Xi Xing, Xianfeng Zengl, S. RaElle Jackson, Tara TeSlaa, Osama Al-Dalahmah, Laith Z. Samarah, Katharine Goodwin, Lifeng Yang, Melanie R. McReynolds, Xiaoxuan Li, Jeremy J. Wolff, Joshua D. Rabinowitz, Shawn M. Davidson
Summary: Isotope imaging enables quantification of metabolic activity in mammalian tissues with spatial resolution, revealing metabolic heterogeneity in the kidney and brain and spatial gradients in metabolic processes.
Article
Biochemical Research Methods
Fiorella C. Grandi, Hailey Modi, Lucas Kampman, M. Ryan Corces
Summary: The ATAC-seq method allows for the detection of unique chromatin landscapes associated with specific cell types without prior knowledge of epigenetic marks or transcription factors. The Omni-ATAC protocol described in this study is optimized for various cell and tissue types and includes detailed steps for library preparation and data analysis.
Article
Biochemical Research Methods
Amr H. Hashem, Salem S. Salem
Summary: This study successfully biosynthesized SeNPs using aqueous extract of Urtica dioica leaf, showing excellent antimicrobial activity and promising anticancer activity. SeNPs exhibited inhibitory activity against various bacteria and fungi, with minimal cytotoxicity towards cancerous cells.
BIOTECHNOLOGY JOURNAL
(2022)
Article
Biochemical Research Methods
Xiujun Zhang, Muhammad Kamran Siddiqui, Sana Javed, Lubna Sherin, Farah Kausar, Mehwish Hussain Muhammad
Summary: Cerium oxide nanoparticles are widely used as catalysts in industry, leading to their significant presence in water systems. This study focuses on analyzing the crystal structure of Ceria Oxide and calculating the Heat of Formation and Entropy using degree-based topological indices. Various topological indices were computed and discussed in relation to the physical properties of the cuprite CeO2 nanocrystal, showing potential for nanoceria engineering.
COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING
(2022)
Article
Biochemical Research Methods
Ying Yang, Lei Chen
Summary: Drug repositioning is a method to discover new therapeutic uses of existing drugs. This study proposed a novel model to identify drug-disease associations by building drug networks, disease networks, and generating features using the Mashup algorithm, and then building the model with the random forest classification algorithm. The model showed good performance with some tests indicating optimal dimensions of drug and disease features for construction.
CURRENT BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Edwin S. Dalmaijer, Camilla L. Nord, Duncan E. Astle
Summary: Cluster algorithms are increasingly used in biomedical research, but there is no established method for calculating a priori statistical power in cluster analysis. Through simulation experiments, we found that clustering outcomes are mainly influenced by large effect sizes or the accumulation of many smaller effects, while differences in covariance structure have little impact. Sufficient statistical power can be achieved with relatively small samples (N = 20 per subgroup) as long as cluster separation is large. Additionally, we demonstrated that fuzzy clustering provides a more parsimonious and powerful alternative for identifying separable multivariate normal distributions.
BMC BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Tuan Nguyen, Giang T T Nguyen, Thin Nguyen, Duc-Hau Le
Summary: This study proposes a novel method called GraphDRP based on graph convolutional networks for drug response prediction and finds that graph representation can improve prediction performance.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Sian Soo Tng, Nguyen Quoc Khanh Le, Hui-Yuan Yeh, Matthew Chin Heng Chua
Summary: This study proposes a deep learning model based on a recurrent neural network (RNN) for predicting histone lysine crotonylation (Kcr) sites in proteins. By embedding the peptide sequences, the efficiency of RNN-based models like LSTM, BiLSTM, and BiGRU networks is investigated. The comparison with other tools and cross-validation tests demonstrate the outstanding performance and computational efficiency of the BiGRU model. A webserver called Sohoko-Kcr is deployed for free use based on the proposed model.
JOURNAL OF PROTEOME RESEARCH
(2022)
Review
Biochemical Research Methods
Haajira Beevi Habeeb Rahuman, Ranjithkumar Dhandapani, Santhoshini Narayanan, Velmurugan Palanivel, Ragul Paramasivam, Ramalakshmi Subbarayalu, Sathiamoorthi Thangavelu, Saravanan Muthupandian
Summary: The search for alternative medicine to combat antibiotic resistance has led to a growing interest in metallic nanoparticles, particularly silver nanoparticles. This review provides a comprehensive understanding of the pharmaceutical qualities of medicinal plants and serves as a convenient guideline for plant-based silver nanoparticles and their antimicrobial activity.
IET NANOBIOTECHNOLOGY
(2022)
Article
Biochemical Research Methods
Johannes Dornhof, Jochen Kieninger, Harshini Muralidharan, Jochen Maurer, Gerald A. Urban, Andreas Weltin
Summary: The study introduced a microfluidic organ-on-chip platform for matrix-based, heterogeneous 3D cell cultures with integrated electrochemical sensors for metabolites. The system allowed precise control of culture conditions and real-time multi-analyte metabolite monitoring, demonstrating potential applications in personalized medicine and cancer research.
Review
Biochemical Research Methods
Mingon Kang, Euiseong Ko, Tesfaye B. Mersha
Summary: High-throughput next-generation sequencing allows for the generation of large amounts of multi-omics data, which has revolutionized biomedical research by providing a more comprehensive understanding of biological systems and disease development mechanisms. Deep learning algorithms have emerged as a promising method in multi-omics data analysis due to their predictive performance and ability to capture nonlinear and hierarchical features. However, integrating and translating multi-omics data into functional insights remains a challenge, but there is a clear trend towards incorporating multi-omics analysis in biomedical research to explain complex relationships between molecular layers.
BRIEFINGS IN BIOINFORMATICS
(2022)
Review
Biochemical Research Methods
Ruiyang Pu, Sha Liu, Xiaoyu Ren, Dian Shi, Yupei Ba, Yanbei Huo, Wenling Zhang, Lingling Ma, Yanyan Liu, Yan Yang, Ning Cheng
Summary: This systematic review evaluates the test accuracy of RT-LAMP and RT-PCR for diagnosing COVID-19. The overall sensitivity of RT-PCR and RT-LAMP was found to be 0.96 and 0.92, respectively, with false-negative rates of 0.06 and 0.12. Subgroup analysis suggests that mixed sampling and multiple target gene diagnosis methods have better diagnostic value. The study shows that RT-PCR and RT-LAMP have high value in diagnosing COVID-19, but there is still a false-negative rate of about 6%-12%.
JOURNAL OF VIROLOGICAL METHODS
(2022)
Article
Biochemical Research Methods
M. A. R. I. A. S. SOARES, L. U. I. S. C. B. SILVA, M. I. G. U. E. L. VIDAL, M. E. D. E. R. I. C. LOYEZ, M. A. R. G. A. R. I. D. A. FACAO, C. H. R. I. S. T. O. P. H. E. CAUCHETEUR, M. A. R. C. E. L. O. E. V. SEGATTO, F. L. O. R. I. N. D. A. M. COSTA, C. A. T. I. A. LEITAO, S. O. N. I. A. O. PEREIRA, N. U. N. O. F. SANTOS, C. A. R. L. O. S. A. F. MARQUES
Summary: Measuring cortisol levels as a stress biomarker is crucial in medical conditions associated with a high risk of metabolic syndromes. Fiber optic biosensors have gained increasing interest due to their ability to detect cortisol with high sensitivity.
BIOMEDICAL OPTICS EXPRESS
(2022)
Article
Biochemical Research Methods
Vivek S. Javalkote, Nagesh Kancharla, Bhaskar Bhadra, Manish Shukla, Badrish Soni, Ajit Sapre, Michael Goodin, Anindya Bandyopadhyay, Santanu Dasgupta
Summary: The COVID-19 pandemic has posed an unprecedented threat to global public health and economies. Scaling up testing for rapid diagnosis of infected patients and quarantine measures are crucial strategies to curb the spread of the virus. Establishing globally accessible diagnostic tests is important for understanding the epidemiology. Recent efforts have focused on utilizing LAMP-based isothermal detection and minimizing reagent requirements to overcome limitations of current tests. Incorporating CRISPR technology with isothermal amplification shows promise for sensitive and rapid detection of SARS-CoV-2 nucleic acids, potentially transforming diagnostics and epidemiology.
Review
Biochemical Research Methods
Soren Richard Stahlschmidt, Benjamin Ulfenborg, Jane Synnergren
Summary: Biomedical data are increasingly multimodal, and deep learning-based data fusion strategies are effective in capturing their complex relationships, especially joint representation learning which models the interactions between different levels of biological organization.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu
Summary: This paper introduces a domain-specific generative Transformer language model BioGPT pre-trained on large-scale biomedical literature, which performs well on biomedical natural language processing tasks, especially achieving high accuracy in relation extraction tasks.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Denis Schapiro, Artem Sokolov, Clarence Yapp, Yu-An Chen, Jeremy L. Muhlich, Joshua Hess, Allison L. Creason, Ajit J. Nirmal, Gregory J. Baker, Maulik K. Nariya, Jia-Ren Lin, Zoltan Maliga, Connor A. Jacobson, Matthew W. Hodgman, Juha Ruokonen, Samouil L. Farhi, Domenic Abbondanza, Eliot T. McKinley, Daniel Persson, Courtney Betts, Shamilene Sivagnanam, Aviv Regev, Jeremy Goecks, Robert J. Coffey, Lisa M. Coussens, Sandro Santagata, Peter K. Sorger
Summary: MCMICRO is a modular and open-source computational pipeline that enables the transformation of highly multiplexed tissue whole-slide images into single-cell data. It is versatile and can be used with various imaging platforms, maintaining spatial context and providing a foundation for the continued development of tissue imaging software.
Article
Biochemical Research Methods
Wei Liu, Hui Lin, Li Huang, Li Peng, Ting Tang, Qi Zhao, Li Yang
Summary: In this study, a new computational method called DFELMDA is proposed to predict miRNA-disease associations using deep forest ensemble learning and autoencoder. Results from experiments on the HMDD dataset show that DFELMDA outperforms other methods in terms of performance.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Cynthia Hajal, Giovanni S. Offeddu, Yoojin Shin, Shun Zhang, Olga Morozova, Dean Hickman, Charles G. Knutson, Roger D. Kamm
Summary: This protocol describes an in vitro model of the human blood-brain barrier, self-assembled within microfluidic devices from stem-cell-derived or primary brain endothelial cells, and primary brain pericytes and astrocytes. The model features relevant cellular organization and morphological characteristics, and can be used to assess pathophysiological molecular transport mechanisms and design targeted therapies for neurological disorders.
Article
Biochemical Research Methods
Jinxian Wang, Xuejun Liu, Siyuan Shen, Lei Deng, Hui Liu
Summary: In this paper, we proposed a deep learning model based on graph neural network and attention mechanism to identify drug combinations that can effectively inhibit the viability of specific cancer cells. The model, called DeepDDS, achieved better performance than other methods in predicting drug synergy. Additionally, we explored the interpretability of the model and found important chemical substructures of drugs. DeepDDS is considered an effective tool for prioritizing synergistic drug combinations for further experimental validation.
BRIEFINGS IN BIOINFORMATICS
(2022)
