27 papers · ranked by Valyu relevance
Ryan N. Gutenkunst, Ryan D. Hernandez, Scott H. Williamson, Carlos D. Bustamante + 1 more
'Carlos D. Bustamante' 'Gil McVean'] Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations.…
Hao Yang, Yao, Angela, Eric H. Chang + 1 more
Contemporary social media platforms enable users to generate and share vast amounts of behavioral data and opinions at an unprecedented scale and granularity. These social media data have been increasingly used in research across various domains, including public opinion analysis(Dong & Lian, 2021; Tavoschi et al.…
Joanne Hinds, Adam N. Joinson, David Garcia
To what extent does our online activity reveal who we are? Recent research has demonstrated that the digital traces left by individuals as they browse and interact with others online may reveal who they are and what their interests may be. In the present paper we report a systematic review that synthesises current…
John A. Kamm, Jonathan Terhorst, Richard Durbin, Yun S. Song
The sample frequency spectrum (SFS), or histogram of allele counts, is an important summary statistic in evolutionary biology, and is often used to infer the history of population size changes, migrations, and other demographic events affecting a set of populations. The expected multipopulation SFS under a given…
Yongsheng Yu, Jiebo Luo
Multimodal Models Authors: ['Yongsheng Yu' 'Jiebo Luo'] Conventional demographic inference methods have predominantly operated under the supervision of accurately labeled data, yet struggle to adapt to shifting social landscapes and diverse cultural contexts, leading to narrow specialization and limited accuracy in…
Florence Parat, Sándor Miklós Szilágyi, Daniel Wegmann, Aurélien Tellier
Inference of demography and mutation rates is of major interest but difficult because genetic data is only informative about the population mutation rate, the product of the effective population size times the mutation rate, and not about these quantities individually. Here we show that this limitation can be overcome…
Drew DeHaas, Zhibai Jia, Leo Speidel, Xinzhu Wei
Accurate parametric inference on complex demographic models is a continuing challenge in population genetics. Ancestral recombination graphs (ARGs) provide richer information than simple population genetic summary statistics and can potentially improve the power and accuracy of such inference. We present mrpast, a tool…
Joane S. Elleouet, Sally N. Aitken
Approximate Bayesian computation (ABC) is widely used to infer demographic history of populations and species using DNA markers. Genomic markers can now be developed for non-model species using reduced representation library (RRL) sequencing methods that select a fraction of the genome using targeted sequence capture…
John Bryant, Tahu Kukutai
populations with limited data Authors: ['John Bryant' 'Tahu Kukutai'] Data on historical populations often extends no further than numbers of people by broad age-sex group, with nothing on numbers of births or deaths. Demographers studying these populations have experimented with methods that use the data on numbers of…
Donna Henderson, Sha (Joe) Zhu, Chris Cole, Gerton Lunter
Demographic events shape a population’s genetic diversity, a process described by the coalescent-with-recombination (CwR) model that relates demography and genetics by an unobserved sequence of genealogies. The space of genealogies over genomes is large and complex, making inference under this model challenging. We…
Arnaud Quelin, Frédéric Austerlitz, Flora Jay
The ever-increasing availability of high-throughput DNA sequences and the development of numerous computational methods have led to considerable advances in our understanding of the evolutionary and demographic history of populations. Several demographic inference methods have been developed to take advantage of these…
Yehezkel S. Resheff, Moni Shahar
Inferring user characteristics such as demographic attributes is of the utmost importance in many user-centric applications. Demographic data is an enabler of personalization, identity security, and other applications. Despite that, this data is sensitive and often hard to obtain. Previous work has shown that purchase…
Soheil Baharian, Simon Gravel
Understanding the historical events that shaped current genomic diversity has applications in historical, biological, and medical research. However, the amount of historical information that can be inferred from genetic data is finite, which leads to an identifiability problem. For example, different historical…
Annabel C. Beichman, Tanya N. Phung, Kirk E. Lohmueller
Inference of demographic history from genetic data is a primary goal of population genetics of model and non-model organisms. Whole genome-based approaches such as the Pairwise/Multiple Sequentially Markovian Coalescent (PSMC/MSMC) methods use genomic data from one to four individuals to infer the demographic history…
Graham Gower, Aaron P Ragsdale, Gertjan Bisschop, Ryan N Gutenkunst + 7 more
'Matthew Hartfield' 'Ekaterina Noskova' 'Stephan Schiffels' 'Travis J Struck' 'Jerome Kelleher' 'Kevin R Thornton' 'G Coop'] Title: Abstract Understanding the demographic history of populations is a key goal in population genetics, and with improving methods and data, ever more complex models are being proposed and…
Nina Cesare, Christan Grant, Quynh C. Nguyen, Hedwig Lee + 1 more
'Elaine O. Nsoesie'] - 1. Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA - 2. School of Computer Science, University of Oklahoma, Norman, OK 73019, USA - 3. Department of Epidemiology and Biostatistics, University of Maryland College Park, MD 20742, USA - 4. Department of…
Sen Li, Mattias Jakobsson
Background The Approximate Bayesian Computation (ABC) approach has been used to infer demographic parameters for numerous species, including humans. However, most applications of ABC still use limited amounts of data, from a small number of loci, compared to the large amount of genome-wide population-genetic data which…
Guoqi Li, Daxuan Zhao, Yi Xu, Shyh-Hao Kuo + 5 more
'Guangshe Zhao' 'Christopher Monterola' 'Zhong-Ke Gao'] In this paper, an entropy-based method is proposed to forecast the demographical changes of countries. We formulate the estimation of future demographical profiles as a constrained optimization problem, anchored on the empirically validated assumption that the…
Robin S. Waples
Recent developments within the IUCN and the Convention on Biological Diversity have affirmed the increasingly key role that effective population size (N*e) and the effective size: census size ratio (N**e/N) play in applied conservation and management of global biodiversity. This paper reviews and synthesizes…
Christopher K. West, Ivy Vecna, Raiyan Chowdhury
The 2021 Canadian census is notable for using a unique form of privacy, random rounding, which independently and probabilistically rounds discrete numerical attribute values. In this work, we explore how hierarchical summative correlation between discrete variables allows for both probabilistic and exact solutions to…
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar
—In the last few years, Artificial Intelligence systems have become increasingly widespread. Unfortunately, these systems can share many biases with human decision-making, including demographic biases. Often, these biases can be traced back to the data used for training, where large uncurated datasets have become the…
Louise M. Arthur, David M. Lawrence, Max Price
We present a comprehensive Bayesian approach to paleodemography, emphasizing the proper handling of uncertainties. We then apply that framework to survey data from Cyprus, and quantify the uncertainties in the paleodemographic estimates to demonstrate the applicability of the Bayesian approach and to show the large…
Authors not listed
Machine learning holds significant promise for accelerating biomarker discovery in clinical proteomics, yet its real-world impact remains limited by widespread methodological pitfalls and unrealistic expectations. In this perspective, we critically examine the integration of machine learning into clinical proteomics…
Luca Maria Pesando, Audrey Dorélien, Xavier St‑Denis, Alexis Santos
This essay provides a series of reflections on the current state of demography as seen by four early-career researchers who are actively engaged in aspects of the discipline as varied as research, teaching, mentorship, data collection efforts, policy making, and policy advising. Despite some claims that the discipline…
Authors not listed
People of color in the United States are disproportionately and unfairly exposed to air pollution. Equity-oriented scientific evaluations quantifying these disparities often use population-average exposure metrics to capture the overall inequality within a system. Utilizing these metrics involves choices about the…
Sarah Chambliss, Carlos Pinon, Kyle Messier, Brian LaFranchi + 5 more
Disparity in air pollution exposure arises from variation at multiple spatial scales: along urbanto-rural gradients, between individual cities within a metropolitan region, within individual neighborhoods, and between city blocks. Here, we improve on existing capabilities to systematically compare urban variation at…
Authors not listed
Levels of fine particulate matter (PM2.5) air pollution in the United States have declined substantially in recent decades, yielding substantial benefits for public health. This study evaluates emission reductions across five key economic sectors—electricity, industrial, transportation, agriculture, and residential—and…