The Kuramoto model, originally proposed to model the dynamics of many interacting oscillators, has been used and generalized for a wide range of applications involving the collective behavior of ...large heterogeneous groups of dynamical units whose states are characterized by a scalar angle variable. One such application in which we are interested is the alignment of orientation vectors among members of a swarm. Despite being commonly used for this purpose, the Kuramoto model can only describe swarms in two dimensions, and hence the results obtained do not apply to the often relevant situation of swarms in three dimensions. Partly based on this motivation, as well as on relevance to the classical, mean-field, zero-temperature Heisenberg model with quenched site disorder, in this paper we study the Kuramoto model generalized toDdimensions. We show that in the important case of three dimensions, as well as for any odd number of dimensions, theD-dimensional generalized Kuramoto model for heterogeneous units has dynamics that are remarkably different from the dynamics in two dimensions. In particular, for oddDthe transition to coherence occurs discontinuously as the interunit coupling constantKis increased through zero, as opposed to theD=2case (and, as we show, also the case of evenD) for which the transition to coherence occurs continuously asKincreases through a positive critical valueKc. We also demonstrate the qualitative applicability of our results to related models constructed specifically to capture swarming and flocking dynamics in three dimensions.
Gene annotation databases (compendiums maintained by the scientific community that describe the biological functions performed by individual genes) are commonly used to evaluate the functional ...properties of experimentally derived gene sets. Overlap statistics, such as Fishers Exact test (FET), are often employed to assess these associations, but don't account for non-uniformity in the number of genes annotated to individual functions or the number of functions associated with individual genes. We find FET is strongly biased toward over-estimating overlap significance if a gene set has an unusually high number of annotations. To correct for these biases, we develop Annotation Enrichment Analysis (AEA), which properly accounts for the non-uniformity of annotations. We show that AEA is able to identify biologically meaningful functional enrichments that are obscured by numerous false-positive enrichment scores in FET, and we therefore suggest it be used to more accurately assess the biological properties of gene sets.
Limited access to testing early in the outbreak, false negative results for nasopharyngeal swabs in early stages of disease, and presentation with gastrointestinal symptoms may have led to some ...patients with COVID-19 being misclassified and placed in non-COVID-19 areas with different infection prevention control processes.3 Enteric features, and the ability of SARS-CoV-2 to persist on surfaces, raise the possibility of faecal-oral transmission in care settings under severe pressure, although the role of this transmission route is uncertain.5 As SARS-CoV-2 is likely to persist as an endemic or seasonal virus in coming years, it is critical to use the lessons learned so far in the pandemic to minimise the burden of hospital-acquired infections, and to consider new approaches to reduce the burden further. Unlike at the beginning of the pandemic, there are opportunities to pre-empt hospital-acquired infections and break chains of transmission through regular patient, resident, and staff testing including point-of-care diagnostics, as recently introduced for NHS staff, coupled with robust hospital infection prevention and control policies that include staff vaccination, environmental disinfection, and appropriate isolation, all supported by sentinel monitoring systems. PJMO reports personal fees for consultancy from Janssen and from the European Respiratory Society; grants from the MRC and Wellcome; funding from the EU and the European Federation of Pharmaceutical Industries and Associations for the respiratory syncytial virus consortium in Europe; and funding from the NIHR, the MRC, and GSK to the EMINENT Network.
Chronic medical conditions show substantial heterogeneity in their clinical features and progression. We develop the novel data-driven, network-based Trajectory Profile Clustering (TPC) algorithm for ...1) identification of disease subtypes and 2) early prediction of subtype/disease progression patterns. TPC is an easily generalizable method that identifies subtypes by clustering patients with similar disease trajectory profiles, based not only on Parkinson's Disease (PD) variable severity, but also on their complex patterns of evolution. TPC is derived from bipartite networks that connect patients to disease variables. Applying our TPC algorithm to a PD clinical dataset, we identify 3 distinct subtypes/patient clusters, each with a characteristic progression profile. We show that TPC predicts the patient's disease subtype 4 years in advance with 72% accuracy for a longitudinal test cohort. Furthermore, we demonstrate that other types of data such as genetic data can be integrated seamlessly in the TPC algorithm. In summary, using PD as an example, we present an effective method for subtype identification in multidimensional longitudinal datasets, and early prediction of subtypes in individual patients.
Jury deliberations provide a quintessential example of collective decision-making, but few studies have probed the available data to explore how juries reach verdicts. We examine how features of jury ...dynamics can be better understood from the joint distribution of final votes and deliberation time. To do this, we fit several different decision-making models to jury datasets from different places and times. In our best-fit model, jurors influence each other and have an increasing tendency to stick to their opinion of the defendant's guilt or innocence. We also show that this model can explain spikes in mean deliberation times when juries are hung, sub-linear scaling between mean deliberation times and trial duration, and unexpected final vote and deliberation time distributions. Our findings suggest that both stubbornness and herding play an important role in collective decision-making, providing a nuanced insight into how juries reach verdicts, and more generally, how group decisions emerge.
The Gene Ontology (GO) provides biologists with a controlled terminology that describes how genes are associated with functions and how functional terms are related to one another. These term-term ...relationships encode how scientists conceive the organization of biological functions, and they take the form of a directed acyclic graph (DAG). Here, we propose that the network structure of gene-term annotations made using GO can be employed to establish an alternative approach for grouping functional terms that captures intrinsic functional relationships that are not evident in the hierarchical structure established in the GO DAG. Instead of relying on an externally defined organization for biological functions, our approach connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different sources. We show that grouping terms by this alternate scheme provides a new framework with which to describe and predict the functions of experimentally identified sets of genes.
The current challenges at the forefront of data-enabled science and engineering require interdisciplinary solutions. Yet most traditional doctoral programs are not structured to support successful ...interdisciplinary research. Here we describe the design of and students’ experiences in the COMBINE (Computation and Mathematics for Biological Networks) interdisciplinary graduate program at the University of Maryland. COMBINE focuses on the development and application of network science methods to biological systems for students from three primary domains: life sciences, computational/engineering sciences, and mathematical/physical sciences. The program integrates three established models (T-shaped, pi-shaped and shield-shaped) for interdisciplinary training. The program components largely fall into three categories: (1) core coursework that provides content expertise, communication, and technical skills, (2) discipline-bridging elective courses in the two COMBINE domains that complement the student’s home domain, (3) broadening activities such as workshops, symposiums, and formal peer-mentoring groups. Beyond these components, the program builds community through both formal and informal networking and social events. In addition to the interactions with other program participants, students engage with faculty in several ways beyond the conventional adviser framework, such as the requirement to select a second out-of-field advisor, listening to guest speakers, and networking with faculty through workshops. We collected data through post-program surveys, interviews and focus groups with students, alumni and faculty advisors. Overall, COMBINE students and alumni reported feeling that the program components supported their growth in the three program objectives of Network Science & Interdisciplinarity, Communication, and Career Preparation, but also recommended ways to improve the program. The value of the program can be seen not only through the student reports, but also through the students’ research products in network science which include multiple publications and presentations. We believe that COMBINE offers an effective model for integrated interdisciplinary training that can be readily applied in other fields.
Crowds can often make better decisions than individuals or small groups of experts by leveraging their ability to aggregate diverse information. Question answering sites, such as Stack Exchange, rely ...on the "wisdom of crowds" effect to identify the best answers to questions asked by users. We analyze data from 250 communities on the Stack Exchange network to pinpoint factors affecting which answers are chosen as the best answers. Our results suggest that, rather than evaluate all available answers to a question, users rely on simple cognitive heuristics to choose an answer to vote for or accept. These cognitive heuristics are linked to an answer's salience, such as the order in which it is listed and how much screen space it occupies. While askers appear to depend on heuristics to a greater extent than voters when choosing an answer to accept as the most helpful one, voters use acceptance itself as a heuristic, and they are more likely to choose the answer after it has been accepted than before that answer was accepted. These heuristics become more important in explaining and predicting behavior as the number of available answers to a question increases. Our findings suggest that crowd judgments may become less reliable as the number of answers grows.
The MYC oncogene has been studied for decades, yet there is still intense debate over how this transcription factor controls gene expression. Here, we seek to answer these questions with an in vivo ...readout of discrete events of gene expression in single cells. We engineered an optogenetic variant of MYC (Pi-MYC) and combined this tool with single-molecule RNA and protein imaging techniques to investigate the role of MYC in modulating transcriptional bursting and transcription factor binding dynamics in human cells. We find that the immediate consequence of MYC overexpression is an increase in the duration rather than in the frequency of bursts, a functional role that is different from the majority of human transcription factors. We further propose that the mechanism by which MYC exerts global effects on the active period of genes is by altering the binding dynamics of transcription factors involved in RNA polymerase II complex assembly and productive elongation.
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•MYC overexpression leads to genome-wide increases in transcription burst duration•MYC globally alters dwell times of general transcription factors•Coupled photoactivation and RNA imaging enables precise measurements of gene regulation
Patange et al. engineered a light-inducible form of the MYC oncogene to directly measure how it modulates transcription in living human cells. Their single-molecule studies show direct evidence of MYC functioning as a global amplifier of transcription, across genes and cell types, by increasing the active period of genes.
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