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Benchmark for quantitative characterization of circadian clock cycles

BIOSYSTEMS 2025年 247卷 105363页

作者： Burckard, Odile Teboul, Michele Delaunay, Franck Chaves, Madalena Univ Cote Azur MACBES Team INRAE CNRSCtr Inria Sophia Antipolis France Univ Cote Azur CNRS INSERM IBV Nice France

Understanding circadian clock mechanisms is fundamental in order to counteract the harmful effects of clock malfunctioning and associated diseases. Biochemical, genetic and systems biology approaches have provided invaluable information on the mechanisms of the circadian clock, from which many mathematical models have been developed to understand the dynamics and quantitative properties of the circadian oscillator. To better analyze and compare quantitatively all these circadian cycles, we propose a method based on a previously proposed circadian cycle segmentation into stages. We notably identify a sequence of eight stages that characterize the progress of the circadian cycle. Next, we apply our approach to an experimental dataset and to five different models, all built with ordinary differential equations. Our method permits to assess the agreement of mathematical model cycles with biological properties or to detect some inconsistencies. As another application of our method, we provide insights on how this segmentation into stages can help to analyze the effect of a clock gene loss of function on the dynamic of a genetic oscillator. The strength of our method is to provide a benchmark for characterization, comparison and improvement of new mathematical models of circadian oscillators in a wide variety of model systems.

关键词： Circadian clock computational method Model comparison Cycle segmentation into stages Algorithm for circadian cycle characterization

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Predicting effective drug combinations for cancer treatment using a graph-based approach

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SYNTHETIC AND SYSTEMS BIOTECHNOLOGY 2025年第1期10卷 148-155页

作者： Wang, Qi Liu, Xiya Yan, Guiying China Agr Univ Coll Sci Beijing 100083 Peoples R China Chinese Acad Sci Acad Math & Syst Sci Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China Chinese Acad Sci Inst Biophys Beijing 100101 Peoples R China

Drug combination therapy, involving the use of two or more drugs, has been widely employed to treat complex diseases such as cancer. It enhances therapeutic efficacy, reduces drug resistance, and minimizes side effects. However, traditional methods to identify effective drug combinations are time-consuming, costly, and less efficient than computational methods. Therefore, developing computational approaches to predict drug combinations has become increasingly important. In this paper, we developed the Random Walk with Restart for Drug Combination (RWRDC) model to predict effective drug combinations for cancer therapy. The RWRDC model offers a quantitative mathematical method for predicting the potential effective drug combinations. Cross-validation results indicate that the RWRDC model outperforms other predictive models, particularly in breast, colorectal, and lung cancer predictions across various performance metrics. We have theoretically proven the convergence of its algorithm and provided an explanation for the algorithm's rationality. A targeted case study on breast cancer further highlights the capability of RWRDC to identify effective drug combinations. These findings highlight our model as a novel and effective tool for discovering potential effective drug combinations, offering new possibilities in therapy. Additionally, the graph-based framework of RWRDC holds potential for predicting drug combinations in other complex diseases, expanding its utility in the medical field.

关键词： Drug combination Cancer therapy computational method Random walk with restart

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Integrative analysis of senescence-related genes identifies robust prognostic clusters with distinct features in hepatocellular carcinoma

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JOURNAL OF ADVANCED RESEARCH 2025年 69卷 107-123页

作者： Liu, Sicheng Meng, Yang Zhang, Yaguang Qiu, Lei Wan, Xiaowen Yang, Xuyang Zhang, Yang Liu, Xueqin Wen, Linda Lei, Xue Zhang, Bo Han, Junhong Sichuan Univ West China Hosp Canc Ctr Dept Biotherapy Chengdu 610041 Peoples R China Sichuan Univ West China Hosp State Key Lab Biotherapy Chengdu 610041 Peoples R China Sichuan Univ West China Hosp Frontiers Sci Ctr Dis Related Mol Network Chengdu 610041 Peoples R China Sichuan Univ West China Hosp Frontiers Sci Ctr Dis Related Mol Network Dept Gen SurgRes Lab Canc Epigenet & Genom Chengdu 610041 Peoples R China

Introduction: Senescence refers to a state of permanent cell growth arrest and is regarded as a tumor suppressive mechanism, whereas accumulative evidence demonstrate that senescent cells play an adverse role during cancer progression. The scarcity of specific and reliable markers reflecting senescence level in cancer impede our understanding of this biological basis. Objectives: Senescence-related genes (SRGs) were collected for integrative analysis to reveal the role of senescence in hepatocellular carcinoma (HCC). methods: Consensus clustering was used to subtype HCC based on SRGs. Several computational methods, including single sample gene set enrichment analysis (ssGSEA), fuzzy c-means algorithm, were performed. Data of drug sensitivities were utilized to screen potential therapeutic agents for different senescence patients. Additionally, we developed a method called signature-related gene analysis (SRGA) for identification of markers relevant to phenotype of interest. Experimental strategies consisting quantitative real-time PCR (qRT-PCR), b-galactosidase assay, western blot, and tumor-T cell co-culture system were used to validate the findings in vitro. Results: We identified three robust prognostic clusters of HCC patients with distinct survival outcome, mutational landscape, and immune features. We further extracted signature genes of senescence clusters to construct the senescence scoring system and profile senescence level in HCC at bulk and single-cell resolution. Senescence-induced stemness reprogramming was confirmed both in silico and in vitro. HCC patients with high senescence were immune suppressed and sensitive to Tozasertib and other drugs. We suggested that MAFG, PLIN3, and 4 other genes were pertinent to HCC senescence, and MAFG potentially mediated immune suppression, senescence, and stemness. Conclusion: Our findings provide insights into the role of SRGs in patients stratification and precision medicine. (c) 2024 The Authors. Published by Els

关键词： Senescence-related genes Hepatocellular carcinoma Prognostic clusters Senescence-associated stemness Therapeutic strategy computational method

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Acquisition of optimal computational solitons for cubic-quartic nonlinear Schrödinger equation through improved Adomian decomposition method

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OPTICAL AND QUANTUM ELECTRONICS 2024年第7期56卷 1250-1250页

作者： Bodaqah, A. M. Al Qarni, A. A. Bakodah, H. O. Alshaery, A. A. Univ Jeddah Fac Sci Dept Math & Stat POB 80327 Jeddah 80327 Saudi Arabia Univ Bisha Coll Sci Dept Math POB 551 Bisha 61922 Saudi Arabia

In this study, we computationally extract the bright, singular and dark optical solitons for the cubic-quartic nonlinear Schr & ouml;dinger equation by using a superior version of Adomian's approach, the improved Adomian decomposition method. Indeed, this reveals approximate closed-form solutions of various forms of Schr & ouml;dinger equations, after splitting the complex-valued solution as a linear combination of two real-valued functions. Moreover, for comparison purposes, some realistic cases of fixed parameter values have been considered for the numerical examination. Notably, the extraction of soliton numerically without the aid of an exact solution stands out to be a remarkable take-home of this study. In addition, some plots and the error tables are reported in the end, where the proposed approach has been shown to enjoy ideal computational accuracy.

关键词： computational method IADM Nonlinear Schr & ouml dinger equation Kerr law nonlinearity Cubic-quartic optical soliton

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computational methods for identifying miRNA sponge interactions

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BRIEFINGS IN BIOINFORMATICS 2017年第4期18卷 577-590页

作者： Thuc Duy Le Zhang, Junpeng Liu, Lin Li, Jiuyong Univ South Australia Sch Informat Technol & Math Sci Mawson Lakes SA 5095 Australia Dali Univ Sch Engn Dali Peoples R China

Recent findings show that coding genes are not the only targets that miRNAs interact with. In fact, there is a pool of different RNAs competing with each other to attract miRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The ceRNAs indirectly regulate each other via the titration mechanism, i.e. the increasing concentration of a ceRNA will decrease the number of miRNAs that are available for interacting with other targets. The cross-talks between ceRNAs, i.e. their interactions mediated by miRNAs, have been identified as the drivers in many disease conditions, including cancers. In recent years, some computational methods have emerged for identifying ceRNA-ceRNA interactions. However, there remain great challenges and opportunities for developing computational methods to provide new insights into ceRNA regulatory mechanisms. In this paper, we review the publically available databases of ceRNA-ceRNA interactions and the computational methods for identifying ceRNA-ceRNA interactions (also known as miRNA sponge interactions). We also conduct a comparison study of the methods with a breast cancer dataset. Our aim is to provide a current snapshot of the advances of the computational methods in identifying miRNA sponge interactions and to discuss the remaining challenges.

关键词： miRNA miRNA sponge interaction ceRNA ceRNA-ceRNA interaction cancer computational method

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computational methods and Applications for Identifying Disease-Associated lncRNAs as Potential Biomarkers and Therapeutic Targets

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MOLECULAR THERAPY-NUCLEIC ACIDS 2020年 21卷 156-171页

作者： Yan, Congcong Zhang, Zicheng Bao, Siqi Hou, Ping Zhou, Meng Xu, Chongyong Sun, Jie Wenzhou Med Univ Sch Biomed Engn Sch Ophthalmol & Optometry Wenzhou 325027 Peoples R China Wenzhou Med Univ Eye Hosp Wenzhou 325027 Peoples R China Wenzhou Med Univ Affiliated Hosp 2 Dept Radiol Wenzhou 325027 Peoples R China

Long non-coding RNAs (lncRNAs) have been recognized as critical components of a broad genomic regulatory network and play pivotal roles in physiological and pathological processes. Identification of disease-associated lncRNAs is becoming increasingly crucial for fundamentally improving our understanding of molecular mechanisms of disease and developing novel biomarkers and therapeutic targets. Considering lower efficiency and higher time and labor cost of biological experiments, computer-aided inference of disease-associated RNAs has become a promising avenue for facilitating the study of lncRNA functions and provides complementary value for experimental studies. In this study, we first summarize data and knowledge resources publicly available for the study of lncRNA-disease associations. Then, we present an updated systematic overview of dozens of computational methods and models for inferring lncRNA-disease associations proposed in recent years. Finally, we explore the perspectives and challenges for further studies. Our study provides a guide for biologists and medical scientists to look for dedicated resources and more competent tools for accelerating the unraveling of disease-associated lncRNAs.

关键词： long non-coding RNAs disease lncRNA-disease association computational method bioinformatics

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computational methodS FOR LOGISTICS PROBLEMS RELATED TO OPTIMAL TREES

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ANZIAM JOURNAL 2017年第3-4期58卷 333-341页

作者： Wu, Longshu Wang, Qin Yang, Xiaobing China Jiliang Univ Coll Sci Hangzhou Zhejiang Peoples R China

In recent years, balanced network optimization problems play an important role in practice, especially in information transmission, industry production and logistics management. In this paper, we consider some logistics optimization problems related to the optimal tree structures in a network. We show that the most optimal subtree problem is NP-hard by transforming the connected dominating set problem into this model. By constructing the network models of the most balanced spanning tree problem with edge set restrictions, and by finding the optimal subtrees in special networks, we present efficient computational methods for solving some logistics problems.

关键词： computational method spanning tree polynomial algorithm nondeterministic polynomial-time (NP)-hard

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computational methods on explosion and impact problems

Computational methods on explosion and impact problems

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International Conference on Heterogeneous Material Mechanics (ICHMM)

作者： Hao, Li Liu, Yan Ning, Jian-guo Ma, Tian-bao Beijing Univ Civil Engn & Architecture Foundat Courses Dept Beijing 100044 Peoples R China

ISBN: (纸本)9781932078800

In this paper, based on Eulerian algorithm of multi-material in cell, computational methods on explosion and impact problems are built, the numerical simulation results of shaped charge jet and the explosive shock wave with or without protective wall are provided. The simulation study indicates that the models and algorithm presented in this paper are reasonable and the computational methods can be used for project design.

关键词： computational method explosion impact

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Frequency range optimization for linear viscoelastic characterization of Burger's model

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INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES 2025年 285卷

作者： Wang, Chen Anupam, Kumar Kasbergen, Cor Erkens, Sandra Delft Univ Technol Fac Civil Engn & Geosci Sect Pavement Engn Stevinweg 1 NL-2628 CN Delft Netherlands

The linear viscoelastic behavior of materials is represented using mechanical models of choice, which are further utilized in different numerical investigations, such as finite element simulations and discrete element simulations. Burger's model is one of the widely adopted mechanical models and remains highly favored in contemporary research due to its multiple advantages. Specifically, it excels in representing long-term creep and stress relaxation behavior in a relatively simplified manner. Accurate identification of the long-term behavior for the viscoelastic material, particularly asphalt concrete, is crucial, as it serves as a key indicator of asphalt pavement performance over its service life. However, past research studies show that the parameters of Burger's model should be back-calculated from experimental data only within a limited range of frequency, otherwise, the parameters fail to represent the true material behavior. To the best of the authors' knowledge, there is no approach for researchers to obtain the critical frequency range in which the experiments should be performed. Therefore, this study proposes a novel framework to find the critical frequency range to obtain appropriate model parameters of Burger's model, to better characterize the viscoelastic behavior of the materials. To examine the framework, asphalt concrete mixtures are used as examples in this study. Necessary laboratory tests including complex modulus tests and stress relaxation tests, are performed on two distinctive types of asphalt concrete mixtures. The generalized Maxwell model with different number of Maxwell chains are used to evaluate the performance of Burger's model. Furthermore, since commercially available finite element packages generally do not have a direct built-in Burger's model, the article shows a way of implementing Burger's model in finite element simulation. The simulations corresponding to the laboratory tests are carried out in both frequency domain and time

关键词： Viscoelastic characterization Constitutive modeling computational method Burger's model Optimal frequency range Stress relaxation

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computational methods for Diagnosability Verification of Hybrid Systems

Computational Methods for Diagnosability Verification of Hyb...

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IEEE Conference on Control and Applications (CCA)

作者： Diene, Oumar Moreira, Marcos V. Alvarez, Victor R. Silva, Eduardo R. Univ Fed Rio de Janeiro Dept Elect Engn Polytech Sch Ilha Fundao Cidade Univ BR-21945970 Rio De Janeiro RJ Brazil Univ Fed Rio de Janeiro COPPE Elect Engn Program Ilha Fundao Cidade Univ BR-21945970 Rio De Janeiro RJ Brazil

ISBN: (纸本)9781479977871

Modern industrial systems are real time controlled and supervised by means of automatic computer-based control systems, combining discrete and continuous behaviors, and are best modeled as hybrid systems (HS). In this paper, two methods for the verification of the diagnosability of hybrid systems are proposed. The first method is based on the construction of a diagnoser automaton, that can also be straightforwardly used for online diagnosis, and the second method is based on a verifier automaton that, although cannot be used for online diagnosis, can be constructed in polynomial time, leading to a smaller computational complexity for the verification of the diagnosability of HS than the method using diagnoser automata. The main idea of the second method is to build a verifier of the underlying discrete-event system (DES), taking into account the distinguishability of the system modes based on the continuous state models of the HS.

关键词： automata theory computational complexity continuous systems discrete event systems modelling DES HS computational method continuous state model diagnosability verification diagnoser automaton discrete-event system hybrid system polynomial time Automata computational modeling Control systems Current measurement Discrete-event systems Fault diagnosis Yttrium discrete event systems hybrid systems computational methods Automata Hydrogen Sulfide (H2S3) control systems Polynomial time AUTOMATA THEORY Electric current measurement Current measuring continuous systems complexity classes DES gene Diethylstilbestrol computational modeling

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