N-terminal proteomics assisted profiling of the unexplored translation initiation landscape in Arabidopsis thaliana

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well-and poorly-annotated genomes

Review of Sex, Ecology, Spirituality by Ken Wilber 2nd ed. 851p (2001)

It is both amazing and fitting that this huge, jargon-laden (this book really needs a glossary!), heavily academic work has become a best seller in the world of the educated. One has to be dedicated to learn the jargon and then plow through 551 pages of text and 238 pages of notes. Meanwhile, we are told time and again that this is just an outline of what is to come! Though he severely criticizes the excesses of the three movements, this is a deconstructive and New Age Mystical and postmodern interpretation of religion, philosophy and the behavioral sciences from a very liberal,spiritual point of view—i.e., without the worst of decon, pm and NAM jargon, rabid egalitarianism and anti-scientific anti-intellectualism. He analyzes in some detail the various world views of philosophy, psychology, sociology and religion, exposing their fatal reductionistic flaws with (mostly) care and brilliance, but most of the sources he analyzes are of almost no relevance today. They use terminology and concepts that were already outdated when he was researching and writing 20 years ago. One has to slog thru endless pages of jargon -laden discussion of Habermas, Kant, Emerson, Jung et.al. to get to the pearls. You get a terrific sampling of bad writing, confused and outdated ideas and obsolete jargon. If one has a good current education, it is doubly painful to read this book (and most writing on human behavior). Painful because it´s so tortured and confusing and then again when you realized how simple it is with modern psychology and philosophy. The terminology and ideas are horrifically confused and dated (but less so in Wilber´s own analysis than in his sources). This book and most of its sources are would-be psychology texts, though most of the authors did not realize it. It is about human behavior and reasoning-about why we think and act the way we do and how we might change in the future. But (like all such discussion until recently) none of the explanations are really explanations, and so they give no insight into human behavior. Nobody discusses the mental mechanisms involved. It is like describing how a car works by discussing the steering wheel and metal and paint without any knowledge of the engine, fuel or drive train. In fact, like most older ´explanations` of behavior, the texts quoted here and the comments by Wilber are often more interesting for what kinds of things they accept (and omit!) as explanations, and the kind of reasoning they use, than for the actual content. If one is up on philosophy and cognitive and evolutionary psychology, most of this is archaic. Like nearly everyone (scholars and public alike--eg, see my review of Dennett´s Freedom Evolves and other books), he does not understand that the basics of religion and ethics-- in fact all human behavior, are programmed into our genes. A revolution in understanding ourselves was taking place while he was writing his many books and it passed him by. Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my article The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in Wittgenstein and Searle 59p(2016). For all my articles on Wittgenstein and Searle see my e-book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Wittgenstein and Searle 367p (2016). Those interested in all my writings in their most recent versions may consult my e-book Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2016 662p (2016). All of my papers and books have now been published in revised versions both in ebooks and in printed books. Talking Monkeys: Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B071HVC7YP. The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle--Articles and Reviews 2006-2016 (2017) https://www.amazon.com/dp/B071P1RP1B. Suicidal Utopian Delusions in the 21st century: Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B0711R5LG

Review of Sex, Ecology, Spirituality by Ken Wilber 2nd ed 851p (2001) (review revised 2019)

please see the full paper for the abstract as the moronic AI used by phil papers won't let me use it as it thinks it has a url in it

Technical Change and Industrial Dynamics as Evolutionary Processes

This work prepared for B. Hall and N. Rosenberg (eds.) Handbook of Innovation, Elsevier (2010), lays out the basic premises of this research and review and integrate much of what has been learned on the processes of technological evolution, their main features and their effects on the evolution of industries. First, we map and integrate the various pieces of evidence concerning the nature and structure of technological knowledge the sources of novel opportunities, the dynamics through which they are tapped and the revealed outcomes in terms of advances in production techniques and product characteristics. Explicit recognition of the evolutionary manners through which technological change proceed has also profound implications for the way economists theorize about and analyze a number of topics central to the discipline. One is the theory of the firm in industries where technological and organizational innovation is important. Indeed a large literature has grown up on this topic, addressing the nature of the technological and organizational capabilities which business firms embody and the ways they evolve over time. Another domain concerns the nature of competition in such industries, wherein innovation and diffusion affect growth and survival probabilities of heterogeneous firms, and, relatedly, the determinants of industrial structure. The processes of knowledge accumulation and diffusion involve winners and losers, changing distributions of competitive abilities across different firms, and, with that, changing industrial structures. Both the sector-specific characteristics of technologies and their degrees of maturity over their life cycles influence the patterns of industrial organization ? including of course size distributions, degrees of concentration, relative importance of incumbents and entrants, etc. This is the second set of topics which we address. Finally, in the conclusions, we briefly flag some fundamental aspects of economic growth and development as an innovation driven evolutionary process.Innovation, Technological paradigms, Technological regimes and trajectories, Evolution, Learning, Capability-based theories of the firm, Selection, Industrial dynamics, Emergent properties, Endogenous growth

Collective Invention during the British Industrial Revolution The Case of the Cornish Pumping Engine

In this paper, we argue that together with individual inventors and firms, what Robert C. Allen (1983) has termed as collective invention settings (that is settings in which rival firms freely release each other pertinent technical information), were also a crucial source of innovation in the industrial revolution period. Until now, this has been very little considered in the literature. This paper focuses on one of these cases: the Cornish mining district. In Cornwall, during the early nineteenth century, a notable collective invention setting, gradually emerged. This case is particularly remarkable because it was capable of generating a continuous and sustained flow of improvements in steam pumping technology which in the end greatly contributed to improve the thermodynamic efficiency of the steam engine. In this paper we study in detail the specific economic circumstances that led to the formation of this collective invention setting and we analyses its consequences for the rate of technological innovationCollective inventions, information sharing, case study

Brewing the future: stylized facts about innovation and their confrontation with a percolation model

innovation, percolation, model

A novel approach integrating ranking functions discovery, optimization and infernce to improve retrieval performance

The significant roles play by ranking function in the performance and success of Information Retrieval (IR) systems and search engines cannot be underestimated. Diverse ranking functions are available in IR literature. However, empirical studies show that ranking functions do not perform constantly well across different contexts (queries, collections, users). In this study, a novel three-stage integrated ranking framework is proposed for implementing discovering, optimizing and inference rankings used in IR systems. The first phase, discovery process is based on Genetic Programming (GP) approach which smartly combines structural and contents features in the documents while the second phase, optimization process is based on Genetic Algorithm (GA) which combines document retrieval scores of various well-known ranking functions. In the 3rd phase, Fuzzy inference proves as soft search constraints to be applied on documents. We demonstrate how these two features are combined to bring new tasks and processes within the three concept stages of integrated framework for effective IR

AUGUR: Forecasting the Emergence of New Research Topics

Being able to rapidly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. The literature presents several approaches to identifying the emergence of new research topics, which rely on the assumption that the topic is already exhibiting a certain degree of popularity and consistently referred to by a community of researchers. However, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge. We address this issue by introducing Augur, a novel approach to the early detection of research topics. Augur analyses the diachronic relationships between research areas and is able to detect clusters of topics that exhibit dynamics correlated with the emergence of new research topics. Here we also present the Advanced Clique Percolation Method (ACPM), a new community detection algorithm developed specifically for supporting this task. Augur was evaluated on a gold standard of 1,408 debutant topics in the 2000-2011 interval and outperformed four alternative approaches in terms of both precision and recall