The challenges and scope of theoretical biology

Scientific theories seek to provide simple explanations for significant empirical regularities based on fundamental physical and mechanistic constraints. Biological theories have rarely reached a level of generality and predictive power comparable to physical theories. This discrepancy is explained through a combination of frozen accidents, environmental heterogeneity, and widespread non-linearities observed in adaptive processes. At the same time, model building has proven to be very successful when it comes to explaining and predicting the behavior of particular biological systems. In this respect biology resembles alternative model-rich frameworks, such as economics and engineering. In this paper we explore the prospects for general theories in biology, and suggest that these take inspiration not only from physics, but also from the information sciences. Future theoretical biology is likely to represent a hybrid of parsimonious reasoning and algorithmic or rule-based explanation. An open question is whether these new frameworks will remain transparent to human reason. In this context, we discuss the role of machine learning in the early stages of scientific discovery. We argue that evolutionary history is not only a source of uncertainty, but also provides the basis, through conserved traits, for very general explanations for biological regularities, and the prospect of unified theories of life.     

Overcoming the Newtonian paradigm: The unfinished project of theoretical biology from a Schellingian perspective

Defending Robert Rosen's claim that in every confrontation between physics and biology it is physics that has always had to give ground, it is shown that many of the most important advances in mathematics and physics over the last two centuries have followed from Schelling's demand for a new physics that could make the emergence of life intelligible. Consequently, while reductionism prevails in biology, many biophysicists are resolutely anti-reductionist. This history is used to identify and defend a fragmented but progressive tradition of anti-reductionist biomathematics. It is shown that the mathematico–physico–chemical morphology research program, the biosemiotics movement, and the relational biology of Rosen, although they have developed independently of each other, are built on and advance this anti-reductionist tradition of thought. It is suggested that understanding this history and its relationship to the broader history of post-Newtonian science could provide guidance for and justify both the integration of these strands and radically new work in post-reductionist biomathematics.     

Vaccinology in the era of high-throughput biology

Vaccination has been tremendously successful saving lives and preventing infections. However, the development of vaccines against global pandemics such as HIV, malaria and tuberculosis has been obstructed by several challenges. A major challenge is the lack of knowledge about the correlates and mechanisms of protective immunity. Recent advances in the application of systems biological approaches to analyse immune responses to vaccination in humans are beginning to yield new insights about mechanisms of vaccine immunity, and to define molecular signatures, induced rapidly after vaccination, that correlate with and predict vaccine induced immunity. Here, we review these advances and discuss the potential of this systems vaccinology approach in defining novel correlates of protection in clinical trials, and in infection-induced ‘experimental challenge models'' in humans.     

Enhancing theoretical understanding of a practical biology course using active and self-directed learning strategies

Laboratories are recognised as central in science education, allowing students to consolidate knowledge and master practical skills, however, their effectiveness has been questioned. Whilst laboratory practicals are useful for students’ learning of basic procedures, they have been shown to be less effective for developing conceptual understanding of the subject. Interactive lectures and bespoke digital resources were utilised in order to enhance theoretical understanding of laboratory practical molecular sessions, thus enabling students to take responsibility for and direct their own learning, encouraging inquiry-based learning. Providing easy to access additional learning resources offered students an opportunity to better prepare themselves for the laboratory, and consolidate their knowledge through subsequent review and self-testing in their own time. Grades before and after implementation of these active learning strategies were analysed to look at the impact on student learning and this study demonstrates that integrating these into a challenging practical biology course improved grades significantly with a concomitant increase in the number of ‘A’ grades attained. Feedback to evaluate use and perceptions of both interactive lectures and digital resources were also analysed. It has been shown here that these activities enhanced student experience and understanding of the course.     

系统生物学和合成生物学研究在生物燃料生产菌株改造中的应用

基于生物质资源生产环境友好的生物燃料,对经济和社会的可持续发展具有重要意义,但其生产成本高的问题十分突出,而高效生产菌株的获得是解决这一问题的根本出路。以下综述了利用系统生物学研究所获得的信息进行菌种改造的过程,重点论述了生产菌株胁迫耐受性方面的研究进展,并讨论了系统生物学、合成生物学和代谢工程技术在改造生物燃料生产菌株中的应用,展望了合成生物学在构建高效生物能源生产菌株方面应用的前景。     

高等师范院校分子生物学课程教学改革与实践

分子生物学是一门从分子水平研究生命现象、生命本质及其规律的科学,是现代生命科学中最具活力的带头学科,掌握分子生物学的基本理论和基本技能已成为21世纪生物科学对人才发展的一个需求。确定科学、合理的教学改革方案,重组、优化教学内容,精心设计教学方法、教学手段及考核方式,对确保分子生物学课程教学质量具有重要意义。结合近年来的分子生物学教学经验,就教材建设、教学内容整合、教学方法改进、课程考核方式、网络课程建设以及开放实验室管理等方面阐述了一些观点和体会,以期为提高分子生物学教学质量及培养素质型人才提供有益参考。     

A day of systems and synthetic biology for non‐experts

From understanding ageing to the creation of artificial membrane‐bounded ‘organisms’, systems biology and synthetic biology are seen as the latest revolutions in the life sciences. They certainly represent a major change of gear, but paradigm shifts? This is open to debate, to say the least. For scientists they open up exciting ways of studying living systems, of formulating the ‘laws of life’, and the relationship between the origin of life, evolution and artificial biological systems. However, the ethical and societal considerations are probably indistinguishable from those of human genetics and genetically modified organisms. There are some tangible developments just around the corner for society, and as ever, our ability to understand the consequences of, and manage, our own progress lags far behind our technological abilities. Furthermore our educational systems are doing a bad job of preparing the next generation of scientists and non‐scientists.     

Building momentum for systems and synthetic biology in India

Biological systems are inherently noisy. Predicting the outcome of a perturbation is extremely challenging. Traditional reductionist approach of describing properties of parts, vis-a-vis higher level behaviour has led to enormous understanding of fundamental molecular level biology. This approach typically consists of converting genes into junk (knock-down) and garbage (knock-out) and observe how a system responds. To enable broader understanding of biological dynamics, an integrated computational and experimental strategy was formally proposed in mid 1990s leading to the re-emergence of Systems Biology. However, soon it became clear that natural systems were far more complex than expected. A new strategy to address biological complexity was proposed at MIT (Massachusetts Institute of Technology) in June 2004, when the first meeting of synthetic biology was held. Though the term ‘synthetic biology’ was proposed during 1970s (Szybalski in Control of gene expression, Plenum Press, New York, 1974), the usage of the original concept found an experimental proof in 2000 with the demonstration of a three-gene circuit called repressilator (Elowitz and Leibler in Nature, 403:335–338, 2000). This encouraged people to think of forward engineering biology from a set of well described parts.     

The congener; A neglected area in the study of behaviour

This paper seeks a deeper understanding of the congener as a factor in animal and human behaviour. It does so, not by concentrating on analyses of stimulus exchanges - largely specific to the species - by which a congener is recognized, but on the more general questions of why a notion of congener exists at all and why it plays such an extraordinary important role in animal and human behaviour.Three separate approaches, by way of anthropomorphic psychology, a paraphysical energy model and the physical theory of the implicate order, lead to the recognition of a certain inseparability of self and congener; and to an interpretation of the content of the notion of congener and of the behaviour in relation to it, in terms of the fundamental concept of energy and the even more fundamental one of order.Dedicated to Professor Gerard P. Baerends, one of my valued guides in ethology.     

Molecular biology in the Soviet Russia (An essay)

Stages of the evolvement and development of the major directions of molecular biology in the 1950–1980’s and its prehistory bracketing the 1920–1940’s are considered against the backgrounds of the history of the Soviet science. Short outlines of the lives and activities of the leading scientists who shaped the directions of and provided for success in studying supramolecular cell structures and molecular mechanisms of processes on a cellular level. This essay, which is far from exhaustive in describing the problems that the Soviet scientists have been dealing with, does not cover the studies of the last decade, nor does it evaluate the contributions of the living molecular biologists.     

基础生物学实验教学改革的构想与实践

针对目前基础生物学实验教学过程中仍然存在着教学内容陈旧、教学模式和考核方式单一等问题,从基础生物学实验教学内容的调整、实验教学模式的创新设计以及多元化考核方式的运用这3个方面阐述了基础生物学实验教学的改革尝试。在教学改革实践过程中遵循“以学生为主体,提高学生综合素质和创新能力”的原则,充分调动学生学习的积极性和主动性,逐步培养学生具备科学探索思维和自主创新的能力。     

Resources, standards and tools for systems biology.

Modelling and simulation techniques are valuable tools for the understanding of complex biological systems. The design of a computer model necessarily has many diverse inputs, such as information on the model topology, reaction kinetics and experimental data, derived either from the literature, databases or direct experimental investigation. In this review, we describe different data resources, standards and modelling and simulation tools that are relevant to integrative systems biology.     

Advancing structural biology through breakthroughs in AI

The past century has witnessed an exponential increase in our atomic-level understanding of molecular and cellular mechanisms from a structural perspective, with multiple landmark achievements contributing to the field. This, coupled with recent and continuing breakthroughs in artificial intelligence methods such as AlphaFold2, and enhanced computational power, is enabling our understanding of protein structure and function at unprecedented levels of accuracy and predictivity. Here, we describe some of the major recent advances across these fields, and describe, as these technologies coalesce, the potential to utilise our enhanced knowledge of intricate cellular and molecular systems to discover novel therapeutics to alleviate human suffering.     

Systems biology in animal sciences

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.     

Inquiry and curiosity in biology

An investigation is described into the interrelations of inquiry-oriented curricula and the development of inquiry skills and scientific curiosity amongst high school students in Israel. Results for whole classes seem to indicate a high correlation between inquiry performance and level of curiosity but this is not reflected in the performance of individuals. Little relationship was found between inquiry-oriented instruction and the development of inquiry skills and scientific curiosity.