Mathematical models to study the biology of pathogens and the infectious diseases they cause

Xavier, João B.; Monk, Jonathan M.; Poudel, Saugat; Norsigian, Charles J.; Sastry, Anand V.; Liao, Chen Chung; Bento, José Maurício Simões; Suchard, Marc A.; Arrieta-Ortiz, Mario L.; Peterson, Eliza J.R.; Baliga, Nitin S.; Stoeger, Thomas; Ruffin, Felicia; Richardson, Reese A.K.; Gao, Catherine; Horvath, Thomas D.; Haag, Anthony M.; Wu, Qinglong; Savidge, Tor; Yeaman, Michael R.

doi:10.1016/j.isci.2022.104079

Cited by 10 publications

(3 citation statements)

References 116 publications

(127 reference statements)

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“…Immunological signatures can manifest across specific study dimensions, such as in certain parts of a dynamic response [1,7], or specific subsets of subjects; recognizing these biological phenomena requires joint analysis of measurements, time points, and patient cohorts. Flattening data limits the datasets to two dimensions and confounds the axes over which flattening occurs, impeding the definition of immunological signatures and their significance.…”

Section: The Multidimensional Challenge Of Systems Immunology Studiesmentioning

confidence: 99%

Tensor-based insights into systems immunity and infectious disease

Chin

Chan

Yeaman

et al. 2023

Trends in Immunology

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Section: The Multidimensional Challenge Of Systems Immunology Studiesmentioning

confidence: 99%

Tensor-based insights into systems immunity and infectious disease

Chin

Chan

Yeaman

et al. 2023

Trends in Immunology

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“…Lasers are widely used for the detection of microorganisms because of high-intensity and monochromatic features. Various light-scattering theories, including Rayleigh theory, Mie scattering, and Rayleigh–Gans theory, have been applied to predict homogeneous particles [ 82 , 83 , 84 , 85 , 86 ]. Modern devices based on light-scattering techniques are designed based on mathematical and physics-related models.…”

Section: Multiangle Laser Light Scatteringmentioning

confidence: 99%

Recent Progress in Spectroscopic Methods for the Detection of Foodborne Pathogenic Bacteria

et al. 2022

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Detection of foodborne pathogens at an early stage is very important to control food quality and improve medical response. Rapid detection of foodborne pathogens with high sensitivity and specificity is becoming an urgent requirement in health safety, medical diagnostics, environmental safety, and controlling food quality. Despite the existing bacterial detection methods being reliable and widely used, these methods are time-consuming, expensive, and cumbersome. Therefore, researchers are trying to find new methods by integrating spectroscopy techniques with artificial intelligence and advanced materials. Within this progress report, advances in the detection of foodborne pathogens using spectroscopy techniques are discussed. This paper presents an overview of the progress and application of spectroscopy techniques for the detection of foodborne pathogens, particularly new trends in the past few years, including surface-enhanced Raman spectroscopy, surface plasmon resonance, fluorescence spectroscopy, multiangle laser light scattering, and imaging analysis. In addition, the applications of artificial intelligence, microfluidics, smartphone-based techniques, and advanced materials related to spectroscopy for the detection of bacterial pathogens are discussed. Finally, we conclude and discuss possible research prospects in aspects of spectroscopy techniques for the identification and classification of pathogens.

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“…Therefore, there exists an imminent and pertinent need to develop systematic and rigorous methods to study microbial interactions [27]. While there are several reviews that have explored the topic [28][29][30], most delve into mathematical equations for network inference with a focus on computational aspects of microbial network construction/ elucidation [31][32][33][34][35]. There is a notable absence of a comprehensive review to pique scientific curiosity of empirical and theoretical scientists alike [36].…”

Section: Introductionmentioning

confidence: 99%

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Srinivasan,

Jnana,

Murali

2024

Microb Ecol

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Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

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Mathematical models to study the biology of pathogens and the infectious diseases they cause

Cited by 10 publications

References 116 publications

Tensor-based insights into systems immunity and infectious disease

Tensor-based insights into systems immunity and infectious disease

Recent Progress in Spectroscopic Methods for the Detection of Foodborne Pathogenic Bacteria

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

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