Quantitative Biology

Accurate numbers are needed to understand and predict viral dynamics. Curation of high-quality literature values for the infectious period duration or household secondary attack rate, for example, is especially pressing currently because these numbers inform decisions about how and when to lockdown or reopen societies. We aim to provide a curated source for the key numbers that help us understand the virus driving our current global crisis. This compendium focuses solely on COVID-19 epidemiology. The numbers reported in summary format are substantiated by annotated references. For each property, we provide a concise definition, description of measurement and inference methods, and associated caveats. We hope this compendium will make essential numbers more accessible and avoid common sources of confusion for the many newcomers to the field such as using the incubation period to denote and quantify the latent period or using the hospitalization duration for the infectiousness period duration. This document will be repeatedly updated and the community is invited to participate in improving it.

The organism is a fundamental concept in biology. However there is no universally accepted, formal, and yet broadly applicable definition of what an organism is. Here we introduce a candidate definition. We adopt the view that the "organism" is a functional concept, used by scientists to address particular questions concerning the future state of a biological system, rather than something wholly defined by that system. In this approach organisms are a coarse-graining of a fine-grained dynamical model of a biological system. Crucially, the coarse-graining of the system into organisms is chosen so that their dynamics can be used by scientists to make accurate predictions of those features of the biological system that interests them, and do so with minimal computational burden. To illustrate our framework we apply it to a dynamic model of lichen symbiosis---a system where either the lichen or its constituent fungi and algae could reasonably be considered "organisms." We find that the best choice for what organisms are in this scenario are complex mixtures of many entities that do not resemble standard notions of organisms. When we restrict our allowed coarse-grainings to more traditional types of organisms, we find that ecological conditions, such as niche competition and predation pressure, play a significant role in determining the best choice for organisms.

We present a completely new version of our arithmetic model of the standard genetic code and compute in a straightforward manner the exact numeric degeneracies of the five multiplets without any trick for the doublets and the sextets, as we have done previously. We give also some interesting applications.

Which part of medicine, if any, can and should be entrusted to AI, now or at some moment in the future? That both medicine and AI will continue to change goes without saying.

In the present article we demonstrate a new hybrid model of tumor growth. Our model is stochastic by tumor population development and strongly deterministic in cell motility dynamics and spatial propagation. In addition, it has excellent extendibility property. Described model is tested on general behavior and on avascular tumor growth case qualitatively.

In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals, both to determine the line of treatment as well as to know the spread of infection to plan containment, mitigation and future responses. However, the lack of adequate testing kits could be a bottleneck, especially in the case of unanticipated new diseases, such as COVID-19, where the testing technology, manufacturing capability, distribution, human skills and laboratories might be unavailable or in short supply. In addition, the cost of the standard PCR test is approximately USD 48, which is prohibitive for poorer patients and most governments. We address this bottleneck by proposing a test methodology that pools the sample from two (or more) patients in a single test. The key insight is that a single negative result from a pooled sample likely implies negative infection of all the individual patients. and It thereby rules out further tests for the patients. This protocol, therefore, requires significantly fewer tests. This may, however, result in somewhat increased false negatives. Our simulations show that combining samples from two patients with 7% underlying likelihood of infection implies that 36% fewer test kits are required, with 14% additional units of time for testing.

Scientific publications enable results and ideas to be transmitted throughout the scientific community. The number and type of journal publications also have become the primary criteria used in evaluating career advancement. Our analysis suggests that publication practices have changed considerably in the life sciences over the past thirty years. More experimental data is now required for publication, and the average time required for graduate students to publish their first paper has increased and is approaching the desirable duration of Ph.D. training. Since publication is generally a requirement for career progression, schemes to reduce the time of graduate student and postdoctoral training may be difficult to implement without also considering new mechanisms for accelerating communication of their work. The increasing time to publication also delays potential catalytic effects that ensue when many scientists have access to new information. The time has come for life scientists, funding agencies, and publishers to discuss how to communicate new findings in a way that best serves the interests of the public and the scientific community.

Worldwide, we are experiencing an unprecedented, accelerated loss of biodiversity triggered by a bundle of anthropogenic threats such as habitat destruction, environmental pollution and climate change. Despite all efforts of the European biodiversity conservation policy, initiated 20 years ago by the Habitats Directive that provided the legal basis for establishing the Natura 2000 network, the goal to halt the decline of biodiversity in Europe by 2010 has been missed. Hochkirch et al. (2013, Conserv. Lett. 6: 462-467) identified four major shortcomings of the current implementation of the directive concerning prioritization of the annexes, conservation plans, survey systems and financial resources. However they did not account for the intended network character of the Natura 2000 sites, an aspect of highest relevance. This response letter deals with this shortcoming as it is the prerequisite, over any other strategies, ensuring a Natura 2020 network being worth its name.

Assessment of the motor activity of group-housed sows in commercial farms. The objective of this study was to specify the level of motor activity of pregnant sows housed in groups in different housing systems. Eleven commercial farms were selected for this study. Four housing systems were represented: small groups of five to seven sows (SG), free access stalls (FS) with exercise area, electronic sow feeder with a stable group (ESFsta) or a dynamic group (ESFdyn). Ten sows in mid-gestation were observed in each farm. The observations of motor activity were made for 6 hours at the first meal or at the start of the feeding sequence, two consecutive days and at regular intervals of 4 minutes. The results show that the motor activity of group-housed sows depends on the housing system. The activity is higher with the ESFdyn system (standing: 55.7%), sows are less active in the SG system (standing: 26.5%), and FS system is intermediate. The distance traveled by sows in ESF system is linked to a larger area available. Thus, sows travel an average of 362 m ± 167 m in the ESFdyn system with an average available surface of 446 m 2 whereas sows in small groups travel 50 m ± 15 m for 15 m 2 available.

The goal of this paper is to advance an extensible theory of living systems using an approach to biomathematics and biocomputation that suitably addresses self-organized, self-referential and anticipatory systems with multi-temporal multi-agents. Our first step is to provide foundations for modelling of emergent and evolving dynamic multi-level organic complexes and their sustentative processes in artificial and natural life systems. Main applications are in life sciences, medicine, ecology and astrobiology, as well as robotics, industrial automation and man-machine interface. Since 2011 over 100 scientists from a number of disciplines have been exploring a substantial set of theoretical frameworks for a comprehensive theory of life known as Integral Biomathics. That effort identified the need for a robust core model of organisms as dynamic wholes, using advanced and adequately computable mathematics. The work described here for that core combines the advantages of a situation and context aware multivalent computational logic for active self-organizing networks, Wandering Logic Intelligence (WLI), and a multi-scale dynamic category theory, Memory Evolutive Systems (MES), hence WLIMES. This is presented to the modeller via a formal augmented reality language as a first step towards practical modelling and simulation of multi-level living systems. Initial work focuses on the design and implementation of this visual language and calculus (VLC) and its graphical user interface. The results will be integrated within the current methodology and practices of theoretical biology and (personalized) medicine to deepen and to enhance the holistic understanding of life.