Here, I argue that computational thinking and techniques are so central to the quest of understanding life that today all biology is computational biology. Computational biology brings order into our understanding of life, it makes biological concepts rigorous and testable, and it provides a reference map that holds together individual insights. The next modern synthesis in biology will be driven by mathematical, statistical, and computational methods being absorbed into mainstream biological training, turning biology into a quantitative science.

A report of BioSysBio 2009, the IET conference on Synthetic Biology, Systems Biology and Bioinformatics, Cambridge, UK, 23-25 March 2009.

The ability to manipulate living organisms is at the heart of a range of emerging technologies that serve to address important and current problems in environment, energy, and health. However, with all its complexity and interconnectivity, biology has for many years been recalcitrant to engineering manipulations. The recent advances in synthesis, analysis, and modeling methods have finally provided the tools necessary to manipulate living systems in meaningful ways and have led to the coining of a field named synthetic biology. The scope of synthetic biology is as complicated as life itself--encompassing many branches of science and across many scales of application. New DNA synthesis and assembly techniques have made routine customization of very large DNA molecules. This in turn has allowed the incorporation of multiple genes and pathways. By coupling these with techniques that allow for the modeling and design of protein functions, scientists have now gained the tools to create completely novel biological machineries. Even the ultimate biological machinery--a self-replicating organism--is being pursued at this moment. The aim of this article is to dissect and organize these various components of synthetic biology into a coherent picture.

Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ∼52-MDa Nuclear Pore Complex, can be mapped with useful accuracy, precision, and completeness. Key challenges in improving integrative modeling include expanding model representations, increasing the variety of input data and prior information, quantifying a match between input information and a model in a Bayesian fashion, inventing more efficient structural sampling, as well as developing better model validation, analysis, and visualization. In addition, two community-level challenges in integrative modeling are being addressed under the auspices of the Worldwide Protein Data Bank (wwPDB). First, the impact of integrative structures is maximized by PDB-Development, a prototype wwPDB repository for archiving, validating, visualizing, and disseminating integrative structures. Second, the scope of structural biology is expanded by linking the wwPDB resource for integrative structures with archives of data that have not been generally used for structure determination but are increasingly important for computing integrative structures, such as data from various types of mass spectrometry, spectroscopy, optical microscopy, proteomics, and genetics. To address the largest of modeling problems, a type of integrative modeling called metamodeling is being developed; metamodeling combines different types of input models as opposed to different types of data to compute an output model. Collectively, these developments will facilitate the structural biology mindset in cell biology and underpin spatiotemporal mapping of the entire cell.

Synthetic biologists come in two broad classes. One uses unnatural molecules to reproduce emergent behaviours from natural biology, with the goal of creating artificial life. The other seeks interchangeable parts from natural biology to assemble into systems that function unnaturally. Either way, a synthetic goal forces scientists to cross uncharted ground to encounter and solve problems that are not easily encountered through analysis. This drives the emergence of new paradigms in ways that analysis cannot easily do. Synthetic biology has generated diagnostic tools that improve the care of patients with infectious diseases, as well as devices that oscillate, creep and play tic-tac-toe.

The inhibitor of nuclear factor-κB (IκB) kinase (IKK) complex is the master regulator of the NF-κB signaling pathway. The activation of the IKK complex is a tightly regulated, highly stimulus-specific, and target-specific event that is essential for the plethora of functions attributed to NF-κB. More recently, NF-κB-independent roles of IKK members have brought increased complexity to its biological function. This review highlights some of the major advances in the studies of the process of IKK activation and the biological roles of IKK family members, with a focus on NF-κB-independent functions. Understanding these complex processes is essential for targeting IKK for therapeutics.

While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.

We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology.

No abstract available

Previous studies have found that students' concept-building approaches, identified a priori with a cognitive psychology laboratory task, are associated with student exam performances in chemistry classes. Abstraction learners (those who extract the principles underlying related examples) performed better than exemplar learners (those who focus on memorizing the training exemplars and responses) on transfer exam questions but not retention questions, after accounting for general ability. We extended these findings to introductory biology courses in which active-learning techniques were used to try to foster deep conceptual learning. Exams were constructed to contain both transfer and retention questions. Abstraction learners demonstrated better performance than exemplar learners on the transfer questions but not on the retention questions. These results were not moderated by indices of crystallized or fluid intelligence. Our central interpretation is that students identified as abstraction learners appear to construct a deep understanding of the concepts (presumably based on abstract underpinnings), thereby enabling them to apply and generalize the concepts to scenarios and instantiations not seen during instruction (transfer questions). By contrast, other students appear to base their representations on memorized instructed examples, leading to good performance on retention questions but not transfer questions.

The molecular pathways that regulate megakaryocyte production have historically been identified through multiple candidate gene approaches. Several transcription factors critical for generating megakaryocytes were identified by promoter analysis of megakaryocyte-specific genes, and their biological roles then verified by gene knockout studies; for example, GATA-1, NF-E2, and RUNX1 were identified in this way. In contrast, other transcription factors important for megakaryopoiesis were discovered through a systems approach; for example, c-Myb was found to be critical for the erythroid versus megakaryocyte lineage decision by genome-wide loss-of-function studies. The regulation of the levels of these transcription factors is, for the most part, cell intrinsic, although that assumption has recently been challenged. Epigenetics also impacts megakaryocyte gene expression, mediated by histone acetylation and methylation. Several cytokines have been identified to regulate megakaryocyte survival, proliferation, and differentiation, most prominent of which is thrombopoietin. Upon binding to its receptor, the product of the c-Mpl proto-oncogene, thrombopoietin induces a conformational change that activates a number of secondary messengers that promote cell survival, proliferation, and differentiation, and down-modulate receptor signaling. Among the best studied are the signal transducers and activators of transcription (STAT) proteins; phosphoinositol-3-kinase; mitogen-activated protein kinases; the phosphatases PTEN, SHP1, SHP2, and SHIP1; and the suppressors of cytokine signaling (SOCS) proteins. Additional signals activated by these secondary mediators include mammalian target of rapamycin; β(beta)-catenin; the G proteins Rac1, Rho, and CDC42; several transcription factors, including hypoxia-inducible factor 1α(alpha), the homeobox-containing proteins HOXB4 and HOXA9, and a number of signaling mediators that are reduced, including glycogen synthase kinase 3α(alpha) and the FOXO3 family of forkhead proteins. More recently, systematic interrogation of several aspects of megakaryocyte formation have been conducted, employing genomics, proteomics, and chromatin immunoprecipitation (ChIP) analyses, among others, and have yielded many previously unappreciated signaling mechanisms that regulate megakaryocyte lineage determination, proliferation, and differentiation. This chapter focuses on these pathways in normal and neoplastic megakaryopoiesis, and suggests areas that are ripe for further study.

No abstract available

The highly A+T rich genomes of human and rodent malarial parasites offer unprecedented glimpses of a lineage that is distinct from other model organisms. Plasmodium is distinguished by the presence of numerous low complexity inserts within globular domains of proteins. It displays several peculiarities in its transcription apparatus, and its DNA repair system appears to favor a certain innate level of mutability. Plasmodium possesses many cell surface molecules with "animal-like" adhesion modules. Potential genetic footprints of the ancestral eukaryotic algal precursor of the apicoplast are also detectable in its genome.

There are widespread aspirations to focus undergraduate biology education on teaching students to think conceptually like biologists; however, there is a dearth of assessment tools designed to measure progress from novice to expert biological conceptual thinking. We present the development of a novel assessment tool, the Biology Card Sorting Task, designed to probe how individuals organize their conceptual knowledge of biology. While modeled on tasks from cognitive psychology, this task is unique in its design to test two hypothesized conceptual frameworks for the organization of biological knowledge: 1) a surface feature organization focused on organism type and 2) a deep feature organization focused on fundamental biological concepts. In this initial investigation of the Biology Card Sorting Task, each of six analytical measures showed statistically significant differences when used to compare the card sorting results of putative biological experts (biology faculty) and novices (non-biology major undergraduates). Consistently, biology faculty appeared to sort based on hypothesized deep features, while non-biology majors appeared to sort based on either surface features or nonhypothesized organizational frameworks. Results suggest that this novel task is robust in distinguishing populations of biology experts and biology novices and may be an adaptable tool for tracking emerging biology conceptual expertise.

No abstract available

Attempts to engage the scientific community to annotate biological data (such as protein/gene function) stored in databases have not been overly successful. There are several hypotheses on why this has not been successful but it is not clear which of these hypotheses are correct. In this study we have surveyed 50 biologists (who have recently published a paper characterizing a gene or protein) to better understand what would make them interested in providing input/contributions to biological databases. Based on our survey two things become clear: a) database managers need to proactively contact biologists to solicit contributions; and b) potential contributors need to be provided with an easy-to-use interface and clear instructions on what to annotate. Other factors such as 'reward' and 'employer/funding agency recognition' previously perceived as motivators was found to be less important. Based on this study we propose community annotation projects should devote resources to direct solicitation for input and streamlining of the processes or interfaces used to collect this input.

A report on the Fifth International Workshop on Bioinformatics and Systems Biology, Berlin, Germany, 22-25 August 2005.

A report of the 3rd International Symposium on Optimization and Systems Biology, 20-22 September 2009, Zhangjiajie, China.

Vasopressins are evolutionarily conserved peptide hormones. Mammalian vasopressin functions systemically as an antidiuretic and regulator of blood and cardiac flow essential for adapting to terrestrial environments. Moreover, vasopressin acts centrally as a neurohormone involved in social and parental behavior and stress response. Vasopressin synthesis in several cell types, storage in intracellular vesicles, and release in response to physiological stimuli are highly regulated and mediated by three distinct G protein coupled receptors. Other receptors may bind or cross-bind vasopressin. Vasopressin is regulated spatially and temporally through transcriptional and post-transcriptional mechanisms, sex, tissue, and cell-specific receptor expression. Anomalies of vasopressin signaling have been observed in polycystic kidney disease, chronic heart failure, and neuropsychiatric conditions. Growing knowledge of the central biological roles of vasopressin has enabled pharmacological advances to treat these conditions by targeting defective systemic or central pathways utilizing specific agonists and antagonists.

Over 35 years ago the cell biology community was introduced to connexins as the subunit employed to assemble semicrystalline clusters of intercellular channels that had been well described morphologically as gap junctions. The decade that followed would see knowledge of the unexpectedly large 21-member human connexin family grow to reflect unique and overlapping expression patterns in all organ systems. While connexin biology initially focused on their role in constructing highly regulated intercellular channels, this was destined to change as discoveries revealed that connexin hemichannels at the cell surface had novel roles in many cell types, especially when considering connexin pathologies. Acceptance of connexins as having bifunctional channel properties was initially met with some resistance, which has given way in recent years to the premise that connexins have multifunctional properties. Depending on the connexin isoform and cell of origin, connexins have wide-ranging half-lives that vary from a couple of hours to the life expectancy of the cell. Diversity in connexin channel characteristics and molecular properties were further revealed by X-ray crystallography and single-particle cryo-EM. New avenues have seen connexins or connexin fragments playing roles in cell adhesion, tunneling nanotubes, extracellular vesicles, mitochondrial membranes, transcription regulation, and in other emerging cellular functions. These discoveries were largely linked to Cx43, which is prominent in most human organs. Here, we will review the evolution of knowledge on connexin expression in human adults and more recent evidence linking connexins to a highly diverse array of cellular functions.