Article
Biochemical Research Methods
Jie Dong, Min-Feng Zhu, Yong-Huan Yun, Ai-Ping Lu, Ting-Jun Hou, Dong-Sheng Cao
Summary: With the explosive growth of data in chemistry and biology, the development of an integrated toolkit to support data mining algorithms is crucial. BioMedR, a freely available R package, offers a comprehensive solution for representing and analyzing molecular objects, providing a wide range of molecular descriptors, fingerprints, and data mining algorithms.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Ragunathan Mariappan, Aishwarya Jayagopal, Ho Zong Sien, Vaibhav Rajan
Summary: In this study, a new approach called Neural Collective Matrix Factorization (NCMF) is introduced for learning effective representations from heterogeneous biomedical data. Through evaluations on tasks such as gene-disease association prediction and adverse drug event prediction, NCMF is found to outperform previous methods and other graph embedding methods in terms of performance.
Article
Biochemistry & Molecular Biology
Emiley A. Eloe-Fadrosh, Faiza Ahmed, Anubhav, Michal Babinski, Jeffrey Baumes, Mark Borkum, Lisa Bramer, Shane Canon, Danielle S. Christianson, Yuri E. Corilo, Karen W. Davenport, Brandon Davis, Meghan Drake, William D. Duncan, Mark C. Flynn, David Hays, Bin Hu, Marcel Huntemann, Julia Kelliher, Sofya Lebedeva, Po-E Li, Mary Lipton, Chien-Chi Lo, Stanton Martin, David Millard, Kayd Miller, Mark A. Miller, Paul Piehowski, Elais Player Jackson, Samuel Purvine, T. B. K. Reddy, Rachel Richardson, Marisa Rudolph, Setareh Sarrafan, Migun Shakya, Montana Smith, Kelly Stratton, Jagadish Chandrabose Sundaramurthi, Pajau Vangay, Donald Winston, Elisha M. Wood-Charlson, Yan Xu, Patrick S. G. Chain, Lee Ann McCue, Douglas Mans, Christopher J. Mungall, Nigel J. Mouncey, Kjiersten Fagnan
Summary: The NMDC Data Portal facilitates exploration and access to multi-omics microbiome data, hosting 10.2 TB of data. The portal utilizes a flexible data schema and workflows to generate annotated data products, offering various interactive search features.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Biochemical Research Methods
Vineet K. Raghu, Xiaoyu Ge, Arun Balajiee, Daniel J. Shirer, Isha Das, Panayiotis Benos, Panos K. Chrysanthis
Summary: Genome sequencing technologies have the potential to transform clinical decision making and biomedical research by enabling high-throughput measurements of the genome at a granular level. It is important to integrate high-throughput genomic data with demographic, phenotypic, environmental, and behavioral information, and infer relationships between these data types for better understanding of disease mechanisms and prediction of medical interventions. A new methodology called piPref-Div has been proposed to select informative variables for probabilistic graphical models, improving breast cancer outcome prediction and providing biologically interpretable views of gene expression data.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Review
Biochemistry & Molecular Biology
Iwona Cicha, Ronny Priefer, Patricia Severino, Eliana B. Souto, Sona Jain
Summary: Biosensor-integrated drug delivery systems are innovative devices that enable continuous monitoring and drug administration, particularly for chronic diseases such as diabetes, cancer, and cardiovascular diseases. The advantages of this technology include high sensitivity and fast drug release.
Article
Biology
Yanan Chen, Rejani B. Kunjamma, Molly Weiner, Jonah R. Chan, Brian Popko
Summary: Enhancing the integrated stress response (ISR) can promote remyelination in inflammatory environments of multiple sclerosis (MS) patients, potentially providing reparative benefits.
Article
Thermodynamics
Huai Su, Lixun Chi, Enrico Zio, Zhenlin Li, Lin Fan, Zhe Yang, Zhe Liu, Jinjun Zhang
Summary: This study develops an intelligent Supply-Demand Side Management method to address challenges posed by highly connected energy systems. By combining customer response analysis, energy network simulation, and the compressibility of natural gas, the method effectively reduces energy load fluctuations and improves system efficiency.
Article
Chemistry, Analytical
Rana Alaa El-deen Ahmed, Manuel Fernandez-Veiga, Mariam Gawich
Summary: Machine learning, especially deep learning with neural networks, has achieved remarkable success in various AI problems. The approach of ML differs from classical engineering and ontologies, as it relies on collecting large datasets and processing them through a generic learning algorithm. Combining ontology-based recommendation and ML-based techniques in a hybrid system is a natural and promising method to enhance semantic knowledge with statistical models. This paper presents a novel hybrid recommendation system that blends knowledge-driven recommendations from an ontology with data-driven recommendations generated by classifiers and a neural collaborative filtering. The authors show that the integration of these two worlds provides measurable improvement and enables the transfer of semantic information to ML and statistical knowledge to the ontology. The proposed system also allows for dynamic behavior capturing by updating the ontology with new products and user behaviors.
Review
Pharmacology & Pharmacy
Li Rong Wang, Limsoon Wong, Wilson Wen Bin Goh
Summary: Machine learning models are widely used in drug development. However, the presence of data doppelgangers can affect the reliability of evaluation methods. This study demonstrates the prevalence of data doppelgangers in biomedical data and provides recommendations to mitigate the doppelganger effect.
DRUG DISCOVERY TODAY
(2022)
Article
Computer Science, Information Systems
Yu Hu, Tiezheng Nie, Derong Shen, Yue Kou, Ge Yu
Summary: Biomedical entity alignment, consisting of entity identification and entity-concept mapping, is crucial in biomedical text mining. The proposed biomedical entity exploring model improves performance by automatically extracting semantic information and aligning entities to the knowledge base, achieving better F1 scores in both tasks.
FRONTIERS OF COMPUTER SCIENCE
(2021)
Article
Automation & Control Systems
Ting Xue, Steven X. Ding, Maiying Zhong, Donghua Zhou
Summary: In this article, an integrated design diagram for a stable kernel representation (SKR)-based data-driven fault detection (FD) system and performance criteria is proposed. The developed FD system is robust against the distributional uncertainties of noises and random faults. Experimental results demonstrate the applicability of the proposed method.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Multidisciplinary
Panagiotis A. Markos, Argyris J. Dentsoras
Summary: The present study introduces a new analytical method for traffic analysis of modern elevator systems. This method probabilistically analyzes the complete operation of any configuration of modern directional collective elevator systems, accommodating various building types and passenger traffic patterns. It has low computational cost and produces results applicable for service performance evaluation and detailed energy consumption analysis.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Education & Educational Research
Ning Zhang, Fan Ouyang
Summary: Collaborative knowledge construction (CKC) involves students sharing information, improving ideas, and constructing collective knowledge. This research used computer-supported collaborative concept mapping activities to facilitate students' CKC process and applied a combined approach of semantic knowledge analysis and learning analytics to extract, analyze, and understand students' knowledge characteristics and evolutionary trends. Results showed that high-performing pairs focused on course-related knowledge and had a relatively stable knowledge evolution trend. This study provides analytical and pedagogical implications for understanding and promoting students' knowledge construction and advancement.
INTERNATIONAL JOURNAL OF EDUCATIONAL TECHNOLOGY IN HIGHER EDUCATION
(2023)
Article
Biochemical Research Methods
Sindhura Thirumal, Amoon Jamzad, Tiziana Cotechini, Charles T. Hindmarch, Charles H. Graham, D. Robert Siemens, Parvin Mousavi
Summary: This article presents an open-source software called TITAN for processing and analyzing Imaging Mass Cytometry (IMC) data. TITAN provides a single environment for image visualization, segmentation, analysis, and export of IMC data, making it more user-friendly compared to current methods.
Article
Biochemical Research Methods
Zhichen Ni, Honglong Chen, Zhe Li, Xiaomeng Wang, Na Yan, Weifeng Liu, Feng Xia
Summary: With the development of AI and IoT, computation intensive and delay sensitive tasks in vehicles pose challenges to driver biometric monitoring. Edge computing offers a solution by offloading tasks to Edge Servers in RSUs, but some tasks may be too complex for ESs. To address this, we propose a collaborative vehicular network where cloud, edge, and terminal cooperate. Vehicles offload computation intensive tasks to the cloud, and we construct a virtual resource pool to integrate resources from multiple ESs. Our proposed MSCET schedule optimizes system utility and outperforms existing schedules according to extensive simulations.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Fedor Kolpakov, Ilya Akberdin, Ilya Kiselev, Semyon Kolmykov, Yury Kondrakhin, Mikhail Kulyashov, Elena Kutumova, Sergey Pintus, Anna Ryabova, Ruslan Sharipov, Ivan Yevshin, Sergey Zhatchenko, Alexander Kel
Summary: BioUML is a web-based integrated platform for systems biology and data analysis. It supports the construction of complex biological models and offers powerful data analysis and visualization capabilities. The platform is also integrated with other tools and plugins to meet various research requirements.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Biochemistry & Molecular Biology
Alexandr Boytsov, Sergey Abramov, Ariuna Z. Aiusheeva, Alexandra M. Kasianova, Eugene Baulin, Ivan A. Kuznetsov, Yurii S. Aulchenko, Semyon Kolmykov, Ivan Yevshin, Fedor Kolpakov, Ilya E. Vorontsov, Vsevolod J. Makeev, Ivan Kulakovskiy
Summary: ANANASTRA is a web server for identifying and annotating regulatory SNPs with allele-specific binding events, aiding researchers in conducting follow-up work on GWAS.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Mathematics
Elena Kutumova, Ilya Akberdin, Ilya Kiselev, Ruslan Sharipov, Fedor Kolpakov
Summary: This article describes a toolkit for presenting physiologically based pharmacokinetic (PBPK) models in a modular graphical view in the BioUML platform. The toolkit is demonstrated using an existing model of nanoparticles delivery to solid tumors in mice, and guidance is provided for converting the PBPK model code from a text modeling language to a visual modular diagram. The proposed approach offers clarity and ease of perception, and reduces the risk of technical errors during model reuse and extension.
Article
Mathematics
Vasiliy N. Afonyushkin, Ilya R. Akberdin, Yulia N. Kozlova, Ivan A. Schukin, Tatyana E. Mironova, Anna S. Bobikova, Viktoriya S. Cherepushkina, Nikolaj A. Donchenko, Yulia E. Poletaeva, Fedor A. Kolpakov
Summary: Patients with COVID-19 may experience multiple organ failure and further research is needed to understand the causes of the disease. This study analyzes published data and conducts original experiments to assess the reproduction of SARS-CoV-2 in different parts of the body. Most viral particles migrate from the nasopharynx to the esophagus, and those entering the gastrointestinal tract lead to infection of the intestinal epithelium and accumulation of the virus in the intestinal lumen. The relatively low concentration of the virus in tissues suggests the importance of viral transportation and redistribution from the nasopharynx and intestines to the lungs. Model simulations also indicate potential use of nasal mucosa sanitation in the early stages of infection.
Review
Biochemistry & Molecular Biology
Elena O. Kutumova, Ilya R. Akberdin, Ilya N. Kiselev, Ruslan N. Sharipov, Vera S. Egorova, Anastasiia O. Syrocheva, Alessandro Parodi, Andrey A. Zamyatnin, Fedor A. Kolpakov
Summary: This article introduces the application of nanomedicine in cancer treatment and the role of physiologically based pharmacokinetic modeling in the design and prediction of therapeutic effects of nanocarriers.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Physiology
Elena Kutumova, Ilya Kiselev, Ruslan Sharipov, Galina Lifshits, Fedor Kolpakov
Summary: This study builds upon a modular agent-based model of the cardiovascular and renal systems to evaluate the efficacy of antihypertensive therapies. The model simulates the response to different mechanisms of action of drugs and has been tested on virtual patients to validate its accuracy. The extended model serves as a foundation for personalized medicine.
FRONTIERS IN PHYSIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Ilya R. R. Akberdin, Konstantin N. N. Kozlov, Fedor V. V. Kazantsev, Stanislav I. I. Fadeev, Vitaly A. A. Likhoshvai, Tamara M. M. Khlebodarova
Summary: Earlier studies found an auto-oscillatory mode of functioning in the metabolism of endogenous nucleoside triphosphates in E. coli cells, which is associated with cell division. A mathematical model of pyrimidine biosynthesis considering negative feedback regulation was developed, showing that both steady-state and oscillatory functioning modes can occur in the system. The occurrence of oscillatory metabolite synthesis depended on the ratio of two parameters: the nonlinearity of UMP effect on carbamoyl-phosphate synthetase activity and the contribution of noncompetitive UTP inhibition to UMP phosphorylation regulation.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Multidisciplinary Sciences
I. N. Kiselev, I. R. Akberdin, F. A. Kolpakov
Summary: SEIR approach is commonly used for studying infectious diseases but suffers from the inability to reproduce observable dynamics of infection. This paper proposes a new modeling approach using time delays and instant transitions to better simulate transition processes and improve parameter identifiability. The approach is applicable not only to Covid-19 but also to other infectious diseases.
SCIENTIFIC REPORTS
(2023)
Review
Biochemistry & Molecular Biology
Alexander Yu. Vertyshev, Ilya R. Akberdin, Fedor A. Kolpakov
Summary: Optimizing muscle aerobic capacity through physical training requires understanding the internal processes that occur during exercise. This review summarizes research on AMPK, CaMKII, and other signaling pathway activities in skeletal muscles during exercise, and proposes a hypothesis that the observed changes in AMPK activity are largely related to metabolic and signaling transients rather than exercise intensity. This hypothesis can help reinterpret existing experimental data and generate ideas for optimizing future training regimens.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
