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An essential goal of program evaluation and scientific research is the investigation of causal mechanisms. Over the past several decades, causal mediation analysis has been used in medical and social sciences to decompose the treatment…

Methodology · Statistics 2016-01-15 K. C. G. Chan , K. Imai , S. C. P. Yam , Z. Zhang

Multiple Sclerosis (MS) is a disorder that usually appears in adults in their thirties. It has a prevalence that ranges between 2 and 150 per 100 000. Epidemiological studies of MS have provided hints on possible causes for the disease…

Subcellular Processes · Quantitative Biology 2013-08-23 Laura Facchini , Alberto Bellin , Eleuterio F. Toro

Mechanical stresses stemming from environmental factors are a key determinant of cellular behavior and physiology. Yet, the role of self-induced biomechanical stresses in growing bacterial colonies has remained largely unexplored. Here, we…

Soft Condensed Matter · Physics 2023-11-27 René Wittmann , G. H. Philipp Nguyen , Hartmut Löwen , Fabian J. Schwarzendahl , Anupam Sengupta

Microbiome `omics approaches can reveal intriguing relationships between the human microbiome and certain disease states. Along with the identification of specific bacteria taxa associated with diseases, recent scientific advancements…

Applications · Statistics 2019-10-07 Shuang Jiang , Guanghua Xiao , Andrew Y. Koh , Qiwei Li , Xiaowei Zhan

The transition from localized to systemic spreading of bacteria, viruses and other agents is a fundamental problem that spans medicine, ecology, biology and agriculture science. We have conducted experiments and simulations in a simple…

Populations and Evolution · Quantitative Biology 2009-11-10 Anna L. Lin , Bernward A. Mann , Gelsy Torres-Oviedo , Bryan Lincoln , Josef Kas , Harry L. Swinney

Causal effect estimation is a critical task in statistical learning that aims to find the causal effect on subjects by identifying causal links between a number of predictor (or, explanatory) variables and the outcome of a treatment. In a…

Methodology · Statistics 2024-11-26 Tathagata Basu , Matthias C. M. Troffaes

The field of active matter explores the behaviors of self propelled agents out of equilibrium, with active suspensions, such as swimming bacteria in solutions, serving as impactful models. These systems exhibit spatio-temporal patterns akin…

Soft Condensed Matter · Physics 2025-08-26 Pratikshya Jena , Shradha Mishra

Causal inference methods can be applied to estimate the effect of a point exposure or treatment on an outcome of interest using data from observational studies. For example, in the Women's Interagency HIV Study, it is of interest to…

Mediation analyses play important roles in making causal inference in biomedical research to examine causal pathways that may be mediated by one or more intermediate variables (i.e., mediators). Although mediation frameworks have been well…

Applications · Statistics 2023-01-25 Meilin Jiang , Seonjoo Lee , James O'Malley , Yaakov Stern , Zhigang Li

This paper studies the problem of globally optimizing a variable of interest that is part of a causal model in which a sequence of interventions can be performed. This problem arises in biology, operational research, communications and,…

Machine Learning · Statistics 2020-05-27 Virginia Aglietti , Xiaoyu Lu , Andrei Paleyes , Javier González

Bacterial communities such as biofilms are widely recognised as being important for survival and persistence of bacteria in harsh environments. Mechanistic models of biofilm growth indicate that the way in which the surface is seeded can…

Quantitative Methods · Quantitative Biology 2007-05-23 Leah R. Johnson

Chlamydia trachomatis (Ct) is the most common bacterial sexually transmitted infection (STI) in the United States and is major cause of infertility, pelvic inflammatory disease, and ectopic pregnancy among women. Despite decades of…

Populations and Evolution · Quantitative Biology 2018-06-14 Asma Azizi Boroojeni

Clinical decisions to treat and diagnose patients are affected by implicit biases formed by racism, ableism, sexism, and other stereotypes. These biases reflect broader systemic discrimination in healthcare and risk marginalizing already…

Machine Learning · Computer Science 2025-01-29 Kara Liu , Russ Altman , Vasilis Syrgkanis

Bacteria are highly adaptive microorganisms that thrive in a wide range of growth conditions via changes in cell morphologies and macromolecular composition. How bacterial morphologies are regulated in diverse environmental conditions is a…

Cell Behavior · Quantitative Biology 2021-10-26 Diana Serbanescu , Nikola Ojkic , Shiladitya Banerjee

Understanding flow and transport of bacteria in porous media is crucial to technologies such as bioremediation, biomineralization or enhanced oil recovery. While physicochemical bacteria filtration is well-documented, recent studies showed…

Soft Condensed Matter · Physics 2022-08-24 Marco Dentz , Adama Creppy , Carine Douarche , Eric Clément , Harold Auradou

The transmission dynamics of Tuberculosis (TB) involve complex epidemiological and socio-economical interactions between individuals living in highly distinct regional conditions. The level of exogenous reinfection and first time infection…

Populations and Evolution · Quantitative Biology 2016-09-15 Victor Moreno , Baltazar Espinoza , Kamal Barley , Marlio Paredes , Derdei Bichara , Anuj Mubayi , Carlos Castillo-Chavez

Bacterial conglomerates such as biofilms and microcolonies are ubiquitous in nature and play an important role in industry and medicine. In contrast to well-mixed, diluted cultures routinely used in microbial research, bacteria in a…

Biological Physics · Physics 2017-01-13 Fred F. Farrell , Matti Gralka , Oskar Hallatschek , Bartlomiej Waclaw

The interventional effects approach to causal mediation analysis is increasingly common in epidemiologic research, given its potential to address policy-relevant questions about hypothetical mediator interventions. Multiple imputation (MI)…

Applied researchers in biomedicine and related fields are often interested in estimating the causal effect of a treatment or intervention. Although randomized clinical trials are considered the gold standard for establishing causal effects,…

Three critical issues for causal inference that often occur in modern, complicated experiments are interference, treatment nonadherence, and missing outcomes. A great deal of research efforts has been dedicated to developing causal…

Methodology · Statistics 2023-04-06 Yuki Ohnishi , Arman Sabbaghi