Constitutive Control: How Experimental Control Strategies Co-Evolved with Biological Knowledge in 19th-Century Physiology

Modern biologists often claim to be committed to a strong reductionist conception of scientific explanation, in contrast to the teleological explanations of medieval natural philosophers. Attention to the actual explanatory strategies used in contemporary biological research, however, reveals a dependence on final cause explanations. A good example can be found in adaptation studies where explanation is typically in terms of optimal design models. Such optimality models are teleological precisely in the way Thomas Aquinas and Albertus Magnus insisted explanation of natural forms must be. Consequently, the non-reductionist conception of final cause defended by Neo-Aristotelian philosophers of science is entirely consistent with common modes of explanation used by contemporary biological researchers.

BackgroundGenome annotation can be viewed as an incremental, cooperative, data-driven, knowledge-based process that involves multiple methods to predict gene locations and structures. This process might have to be executed more than once and might be subjected to several revisions as the biological (new data) or methodological (new methods) knowledge evolves. In this context, although a lot of annotation platforms already exist, there is still a strong need for computer systems which take in charge, not only the primary annotation, but also the update and advance of the associated knowledge. In this paper, we propose to adopt a blackboard architecture for designing such a systemResultsWe have implemented a blackboard framework (called Genepi) for developing automatic annotation systems. The system is not bound to any specific annotation strategy. Instead, the user will specify a blackboard structure in a configuration file and the system will instantiate and run this particular annotation strategy. The characteristics of this framework are presented and discussed. Specific adaptations to the classical blackboard architecture have been required, such as the description of the activation patterns of the knowledge sources by using an extended set of Allen's temporal relations. Although the system is robust enough to be used on real-size applications, it is of primary use to bioinformatics researchers who want to experiment with blackboard architectures.ConclusionIn the context of genome annotation, blackboards have several interesting features related to the way methodological and biological knowledge can be updated. They can readily handle the cooperative (several methods are implied) and opportunistic (the flow of execution depends on the state of our knowledge) aspects of the annotation process.

Review: <i>Molecular Capture: The Animation of Biology</i>, by Adam Nocek

This review discusses some of the recent developments in genomics and its current and future relevance for veterinary pharmacology and toxicology. With the rapid progress made in this field several new approaches in pharmacological and toxicological research have developed and drug discovery and drug development strategies have changed dramatically. In this review, the term genomics is used to encompass the three sub-disciplines transcriptomics, proteomics and metabolomics (or metabonomics) to describe the formation and fate of mRNA, proteins and metabolites, respectively. The current status and methods of the technology and some applications are briefly described. Although the DNA sequencing programmes are receiving considerable attention, the real value of genomics for pharmacology and toxicology is brought by the parallel developments in bio-informatics, bio-statistics and the integration of biology with mathematics and information technology. The ultimate level of integration is now mostly called systems biology, where mRNA, proteins and metabolites are being analysed in parallel, using a complete arsenal of analytical techniques (DNA-array, LC-MS/MS, GC-MS/MS, NMR, etc.). The information thus collected is analysed, integrated, linked to database information and translated to pathways and systems. This approach offers an enormous potential to study disease mechanisms and find new drug targets. Thus far, genomics and systems biology have not been introduced significantly in typical veterinary pharmacological and toxicological research programmes. The high costs and complexity connected to these large projects often form major obstacles for research groups with limited budgets. In other veterinary areas and disciplines, including infectious diseases, animal production and food-safety more examples of application are available. Genomics and bio-informatics provide outstanding opportunities to study pharmacology and toxicology in a more holistic way, taking into account the complexity of biological systems and based on the basic principles of physiology and the concept of homeostasis. Knowledge of biology, in vivo and in vitro models, and comparative pharmacology/toxicology is essential here, creating excellent opportunities for the veterinary trained scientist.

as part of a continuing effort to integrate physiology and genomics, the American Physiological Society sponsored a meeting at the Riverfront Augusta Hotel in Augusta, Georgia, October 1–4, 2003, titled “Understanding Renal and Cardiovascular Function through Physiological Genomics.” Organized

Interdisciplinary Graduate Education: A Case Study

BackgroundSingle-molecule techniques have emerged as incisive approaches for addressing a wide range of questions arising in contemporary biological research [Trends Biochem Sci 38:30–37, 2013; Nat Rev Genet 14:9–22, 2013; Curr Opin Struct Biol 2014, 28C:112–121; Annu Rev Biophys 43:19–39, 2014]. The analysis and interpretation of raw single-molecule data benefits greatly from the ongoing development of sophisticated statistical analysis tools that enable accurate inference at the low signal-to-noise ratios frequently associated with these measurements. While a number of groups have released analysis toolkits as open source software [J Phys Chem B 114:5386–5403, 2010; Biophys J 79:1915–1927, 2000; Biophys J 91:1941–1951, 2006; Biophys J 79:1928–1944, 2000; Biophys J 86:4015–4029, 2004; Biophys J 97:3196–3205, 2009; PLoS One 7:e30024, 2012; BMC Bioinformatics 288 11(8):S2, 2010; Biophys J 106:1327–1337, 2014; Proc Int Conf Mach Learn 28:361–369, 2013], it remains difficult to compare analysis for experiments performed in different labs due to a lack of standardization.ResultsHere we propose a standardized single-molecule dataset (SMD) file format. SMD is designed to accommodate a wide variety of computer programming languages, single-molecule techniques, and analysis strategies. To facilitate adoption of this format we have made two existing data analysis packages that are used for single-molecule analysis compatible with this format.ConclusionAdoption of a common, standard data file format for sharing raw single-molecule data and analysis outcomes is a critical step for the emerging and powerful single-molecule field, which will benefit both sophisticated users and non-specialists by allowing standardized, transparent, and reproducible analysis practices.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-014-0429-4) contains supplementary material, which is available to authorized users.

Collecting, comparing, and computing molecular sequences are among the most prevalent practices in contemporary biological research. They represent a specific way of producing knowledge. This paper explores the historical development of these practices, focusing on the work of Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley, who produced the first computer-based collection of protein sequences, published in book format in 1965 as the Atlas of Protein Sequence and Structure. While these practices are generally associated with the rise of molecular evolution in the 1960s, this paper shows that they grew out of research agendas from the previous decade, including the biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code. It also shows how computers became essential for the handling and analysis of sequence data. Finally, this paper reflects on the relationships between experimenting and collecting as two distinct "ways of knowing" that were essential for the transformation of the life sciences in the twentieth century.

Studying the ultra-fine structures and functions of the subcellular organelles and exploring the dynamic biological events in depth are the key issues in contemporary biological research. Fluorescence bio-imaging has been used to study cell biology for decades. However, the structures and functions of the subcellular organelles which fall under the diffraction limit are still not explored fully at a nanoscale level. Several super-resolution microscopy (SRM) techniques have been devised over the years which can be utilized to overcome diffraction limit. These techniques have opened a new window in biological research. However, SRM methods are highly vulnerable to the lack of appropriate fluorophores and other sophisticated technical considerations. Therefore, this chapter briefly summarizes the basic principles of various SRM methods which have been frequently utilized in biological imaging. The chapter not only gives an overview of the technical advantages and drawbacks about using different SRM techniques for bio-imaging applications but also briefly articulates the nitty-gritties of selecting a proper fluorescent probe for a specific SRM experiment with biological samples.

In contemporary biological research and applications, control systems have become indispensable for understanding and managing the intricate dynamics of the human biological system. Given the critical role of components such as the pancreas structure, protein formation, insulin and glucose regulation, and the genetic regulatory network (GRN), any disturbances in these systems can lead to severe health issues. To overcome these issues, to introduced a novel hybrid controller called the fuzzy lion‐based optimized fractional order system (FL‐OFOS) for evaluating the performance of the system. This controller aims to efficiently govern and regulate key components of the human biological system, including insulin dynamics, protein synthesis, pancreas functionality, and GRN management. The controller is specifically tailored to regulate insulin, protein synthesis, pancreas function, and GRN dynamics within the human biological system. The optimization of biological parameter values is achieved through the incorporation of the fuzzy lion function. The results of this study highlight the efficacy of the FL‐OFOS controller in optimizing and regulating various biological parameters. The system demonstrates minimal error rates, rapid response times, reduced overshoot, and high control precision and accuracy. The proposed controller achieves a minimal error rate of 0.98%, with only minor overshoot occurring in the outcomes. As a result, the FL‐OFOS controller offers substantial gains and delivers optimal results in the realm of biological systems.

Today, developmental genes are at the focus of attention of many developmental biologists as well as evolutionary biologists and paleontologists. The formation of the concept of developmental genes progressed stepwise during the twentieth century. However, the significance of these genes was not fully recognized until the end of the 1980s when, thanks to new genetic engineering techniques, homologous genes were isolated from very different organisms, ranging from Drosophila or nematodes to mammals and humans. Such genes are highly conserved. The proteins encoded by developmental genes are transcription factors that regulate the expression of other genes and components of the cellular signaling pathways that allow cells to communicate with their neighbors. Frequently, the conservation is not limited to one gene but extends to the entire pathway. The significance of these genes remains puzzling: Their functions during development are difficult to state precisely, as well as the role they play in the evolutionary shifts such as the Cambrian explosion. Are they the master genes that guide development and constrain evolution or only the toolbox with which evolution tinkers? The very notation of developmental genes appears increasingly problematic. The concept of the developmental gene occupies a central position in contemporary biological research at the crossroads between developmental and evolutionary biology. In this brief text, I would like to outline the major steps that led to the formation of this concept and emphasize some of the difficulties encountered by biologists in its present-day use.

Strategies for multigene expression in eukaryotic cells

Umberto echo

Aquinas famously held that only intellectual beings can grasp the natures or essences of things and cognize universals per se. Below these intellectual beings, however, were the non-human animals who shared many of the interior sense faculties in common with man; such animals’ highest sense was merely what is called the estimative power. Aquinas’s account of animal cognition has largely been ignored in contemporary biological research, although hopes for a resurgence have been emerging in the Thomistic world. In this paper I seek to explicate Aquinas’s account of animal cognitive activities, particularly by explicating a more detailed account of animal cognitive action as found in the biological works of Aristotle known by Aquinas. I then turn to various contemporary biological findings to show that many purported modern discoveries (like dolphins rescuing a man or recognition of social hierarchies) shouldn’t be so surprising after all. Many such cognitive acts were already there in the texts of Aristotle read by Aquinas.

Anna Lowenhaupt Tsing opens her book by discussing the enlightenment paradigm that relegated nature as passive background and resources for humans to extract and profit from. She states that previously it was mainly non-western storytellers who explored the realm of interconnection between all beings, human and non-human alike. This notion of ‘interspecies entanglement’ has become a growing topic within contemporary biological research thus destabilising modernist assumptions that place humans at the forefront of knowledge and perceived value (Tsing, 2015, p. vii).