English Title: Time and scansion: rythmical meaning of Duration between Husserl and Bachelard. -/- Abstract: Inside phenomenological search, present time and instant live inside a troubled dialectic: for Husserl present runs, widening out past and future, in the same moment, like the Heraclitean bowstring which stretches between two dimensions. Gaston Bachelard, on the contrary, is the thinker of Discreteness, where temporal continuum is linked to the reciprocal differentiating of instants in the duration. So, the conceptions of time inside these philosophers (...) seem to be opposed one to the other, but inside these two modalities of scansion we meet a steady thread, which underlies both the interpretations, which precipitate one on the other. Let’s read the taking shape of the positions inside La dialectique de la durée (1936) and in Husserl’s writings on attention, linked to the rise of an aspect of the thing above the others (1904 -1905) treated in Husserliana XXXVIII (Wahrnehmung und Aufmerksamkeit, Texte aus dem Nachlass, (1893 – 1912). /// -/- Resumen: En la investigación fenomenológica los conceptos de instante y presente viven in potente una abierta tensión constitutiva: en la filosofía de Husserl es el presente el que transcurre, dilatándose conjuntamente hacia el pasado y el futuro como la heraclítea cuerda del arco, que se extiende entre los dos lados de una dirección unitaria y continua. Gaston Bachelard, por el contrario, es un pensador de la discreción, no existe un continuo temporal sino una gran sutura en la que los instantes se diferencian en la duración. Las concepciones del tiempo entre los dos filósofos parecen oponerse la una a la otra y, sin embargo, entre las dos formas de escansión, existe un hilo firme, que ciñe las dos interpretaciones, haciéndolas precipitar una dentro de la otra, en nombre del contenido perceptivo. Las dos posiciones emergen con su diferencia en La dialéctica de la duración [1936] y en los textos que Husserl ha dedicado al tema de la atención y el interés [1898; 1904; 1905]. -/- . (shrink)

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to (...) existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource providing details on the people, policies, and issues being addressed in association with OBI. (shrink)

Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value from data sets (...) them. However, such ‘minimum information’ MI checklists are usually developed independently by groups working within representatives of particular biologically- or technologically-delineated domains. Consequently, an overview of the full range of checklists can be difficult to establish without intensive searching, and even tracking thetheir individual evolution of single checklists may be a non-trivial exercise. Checklists are also inevitably partially redundant when measured one against another, and where they overlap is far from straightforward. Furthermore, conflicts in scope and arbitrary decisions on wording and sub-structuring make integration difficult. This presents inhibit their use in combination. Overall, these issues present significant difficulties for the users of checklists, especially those in areas such as systems biology, who routinely combine information from multiple biological domains and technology platforms. To address all of the above, we present MIBBI (Minimum Information for Biological and Biomedical Investigations); a web-based communal resource for such checklists, designed to act as a ‘one-stop shop’ for those exploring the range of extant checklist projects, and to foster collaborative, integrative development and ultimately promote gradual integration of checklists. (shrink)

A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing (...) a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion. We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies. Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data. (shrink)

The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one trait approch, which (...) has often proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology has taken off. Systems biology [Noble, 2006] emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based upon linear causal chains (e.g. gene → behaviour). Mathematical modelling is one the favourite tools of systems biologists to analyze the possible effects of competing negative and positive feedback loops which can be observed at several levels (from molecules to organelles, cells, tissues, organs, organisms, ecosystems). Systems biology is by now a well-established field, as it can be inferred by the rapid growth in number of conferences and journals devoted to it, as well as by the existence of several grants and funded projects.Systems biology is mainly focused upon the description of specific biological items, like for example specific organisms, or specific organs in a class of animals, or specific genetic-metabolic circuits. It therefore leaves open the issue of the search for general principles of biological organization, which apply to all living beings or to at least to broad classes. We know indeed that there are some principles of this kind, biological evolution being the most famous one. The theory of cellular organization also qualifies as a general principle. But the main focus of biological research has been that of studying specific cases, with some reluctance to accept (and perhaps a limited interest for) broad generalizations. This may however change, and this is indeed the challenge of complex systems biology: looking for general principles in biological systems, in the spirit of complex systems science which searches for similar features and behaviours in various kinds of systems. The hope to find such general principles appears well founded, and I will show in Section 2 that there are indeed data which provide support to this claim. Besides data, there are also general ideas and models concerning the way in which biological systems work. The strategy, in this case, is that of introducing simplified models of biological organisms or processes, and to look for their generic properties: this term, borrowed from statistical physics, is used for those properties which are shared by a wide class of systems. In order to model these properties, the most effective approach has been so far that of using ensembles of systems, where each member can be different from another one, and to look for those properties which are widespread. This approach was introduced many years ago [Kauffman, 1971] in modelling gene regulatory networks. At that time one had very few information about the way in which the expression of a given gene affects that of other genes, apart from the fact that this influence is real and can be studied in few selected cases (like e.g. the lactose metabolism in E. coli). Today, after many years of triumphs of molecular biology, much more has been discovered, however the possibility of describing a complete map of gene-gene interactions in a moderately complex organism is still out of reach. Therefore the goal of fully describing a network of interacting genes in a real organism could not be (and still cannot be) achieved. But a different approach has proven very fruitful, that of asking what are the typical properties of such a set of interacting genes. Making some plausible hypotheses and introducing some simplifying assumptions, Kauffman was able to address some important problems. In particular, he drew attention to the fact that a dynamical system of interacting genes displays selforganizing properties which explain some key aspects of life, most notably the existence of a limited number of cellular types in every multicellular organism (these numbers are of the order of a few hundreds, while the number of theoretically possible types, absent interactions, would be much much larger than the number of protons in the universe). In section 3 I will describe the ensemble based approach in the context of gene regulatory networks, and I will show that it can describe some important experimental data. Finally, in section 4 I will discuss some methodological aspects. (shrink)

L'esistenza del commento di Alessandro di Afrodisia al De generatione aristotelico, perduto nella versione greca e nella traduzione araba, è attestata da numerose fonti arabe, tra le quali Averroè, nel suo commento alla stessa opera. L'A. rintraccia la presenza, la tipologia e la distribuzione delle citazioni tratte dal commento di Alessandro nel Kitab al-Tasrif, un'opera del corpus alchemico attribuita a Gabir ibn Hayyan. Secondo l'A., la sezione interessata dalle citazioni assembla tre diversi tipi di testi: 1) lemmi del De generatione (...) in traduzione araba; 2) frammenti lacunosi della traduzione araba del commento di Alessandro; 3) interventi di collegamento. Una più ampia discussione si trova in un saggio visibile sulla pagina "publicationslist" dell'autore: "Alessandro di Afrodisia sulle 'contrarietà tangibili' (De gen. et corr. II.2): fonti greche e arabe a confronto" in: Aristotele e Alessandro di Afrodisia nella tradizione araba, a c. di C. D'Ancona e G. Serra, “Il Poligrafo”, Padova 2002, pp. 151-189. Notasi che il testo ricostruito di Alessandro in GC 2.2-5 è stato pubblicato da E. Gannagé nella serie ACA, che però non menziona il contributo di SF, dalla cui iniziativa, dalle cui analisi e dalla cui ricostruzione integrale, svolta sul manoscritto arabo Paris. 5099, la ricerca prese l'avvio. (shrink)

Arthur Danto asserts that Maya Lin’s Vietnam Veterans Memorial in Washington really embodies the beauty of his meaning. For him, the Memorial’s “internal beauty” is felt and read because she is built as a text by the rhetoric of enthymeme, as a syllogism based on some tacit knowledges and highly probables communplaces. However, the relationship to the Kant’s pulchritudo adhaerens and philosophy of architecture is not an easy one : Danto rejects as unreadable the self-referent formalism of Greenberg’s Modernism and (...) the environmental non-monumentality of Richard Serra’s Minimalism, but the agency of the Memorial’s shared internal beauty is haunted by an unquestioned spectral logic. Actually, the image embodiment in this work can always exceed the rhetoric of reconnaissance supported by the syllogistic rhetoric and disturb the identity framework of the nord-american community. The beholders’ reflecting shape on the Memorial can become, finally, an unreadable and pathetic index, or be perceived as a figural imprint, ephemeral and troubling ; these disembodied pictures can achieve a medial incarnation – e.g. a Verkörperung – of the underworld. (shrink)

Arthur Danto asserts that Maya Lin’s Vietnam Veterans Memorial in Washington embodies the rhetoric paradigm of internal beauty’s meaning. However, the relationship to the Kant’s pulchritudo adhaerens is not an easy one: Danto’s recalls against the self-referent formalism of Greenberg’s Modernism and his tacit issues about the environmental non-monumentality of Richard Serra’s Minimalism, are, most importantly, haunted by the unquestioned spectral logic of the image embodiment. The beholders’ reflecting shape on the funeral Wall is, finally, both a pathetic index (...) and a medial incarnation–e.g. a Verkörperung–of the underworld. (shrink)

The enormous increasing of connections between people and the noteworthy enlargement of domains and methods in sciences have augmented extraordinarily the cardinality of the set of meaningful human symbols. We know that complexity is always on the way to become complication, i.e. a non-tractable topic. For this reason scholars engage themselves more and more in attempting to tame plurality and chaos. In this book distinguished scientists, philosophers and historians of science reflect on the topic from a multidisciplinary point of view. (...) Is it possible to dominate complexity through reductionism? Are there other conceptual instruments useful to take account of complexity? What is complexity in biology, mathematics, physics and philosophy of mind? These are some of the questions which are faced in this volume. (shrink)