ISOL@: an Italian SOLAnaceae genomics resource

BACKGROUND: Present-day '-omics' technologies produce overwhelming amounts of data which include genome sequences, information on gene expression (transcripts and proteins) and on cell metabolic status. These data represent multiple aspects of a biological system and need to be investigated as a whole to shed light on the mechanisms which underpin the system functionality.The gathering and convergence of data generated by high-throughput technologies, the effective integration of different data-sources and the analysis of the information content based on comparative approaches are key methods for meaningful biological interpretations.In the frame of the International Solanaceae Genome Project, we propose here ISOLA, an Italian SOLAnaceae genomics resource. RESULTS: ISOLA (available at http://biosrv.cab.unina.it/isola) represents a trial platform and it is conceived as a multi-level computational environment.ISOLA currently consists of two main levels: the genome and the expression level. The cornerstone of the genome level is represented by the Solanum lycopersicum genome draft sequences generated by the International Tomato Genome Sequencing Consortium. Instead, the basic element of the expression level is the transcriptome information from different Solanaceae species, mainly in the form of species-specific comprehensive collections of Expressed Sequence Tags (ESTs).The cross-talk between the genome and the expression levels is based on data source sharing and on tools that enhance data quality, that extract information content from the levels' under parts and produce value-added biological knowledge. CONCLUSIONS: ISOLA is the result of a bioinformatics effort that addresses the challenges of the post-genomics era. It is designed to exploit '-omics' data based on effective integration to acquire biological knowledge and to approach a systems biology view. Beyond providing experimental biologists with a preliminary annotation of the tomato genome, this effort aims to produce a trial computational environment where different aspects and details are maintained as they are relevant for the analysis of the organization, the functionality and the evolution of the Solanaceae family

The emergence of commercial genomics: analysis of the rise of a biotechnology subsector during the Human Genome Project, 1990 to 2004.

BackgroundDevelopment of the commercial genomics sector within the biotechnology industry relied heavily on the scientific commons, public funding, and technology transfer between academic and industrial research. This study tracks financial and intellectual property data on genomics firms from 1990 through 2004, thus following these firms as they emerged in the era of the Human Genome Project and through the 2000 to 2001 market bubble.MethodsA database was created based on an early survey of genomics firms, which was expanded using three web-based biotechnology services, scientific journals, and biotechnology trade and technical publications. Financial data for publicly traded firms was collected through the use of four databases specializing in firm financials. Patent searches were conducted using firm names in the US Patent and Trademark Office website search engine and the DNA Patent Database.ResultsA biotechnology subsector of genomics firms emerged in parallel to the publicly funded Human Genome Project. Trends among top firms show that hiring, capital improvement, and research and development expenditures continued to grow after a 2000 to 2001 bubble. The majority of firms are small businesses with great diversity in type of research and development, products, and services provided. Over half the public firms holding patents have the majority of their intellectual property portfolio in DNA-based patents.ConclusionsThese data allow estimates of investment, research and development expenditures, and jobs that paralleled the rise of genomics as a sector within biotechnology between 1990 and 2004

The Family Name as Socio-Cultural Feature and Genetic Metaphor: From Concepts to Methods

A recent workshop entitled The Family Name as Socio-Cultural Feature and Genetic Metaphor: From Concepts to Methods was held in Paris in December 2010, sponsored by the French National Centre for Scientific Research (CNRS) and by the journal Human Biology. This workshop was intended to foster a debate on questions related to the family names and to compare different multidisciplinary approaches involving geneticists, historians, geographers, sociologists and social anthropologists. This collective paper presents a collection of selected communications

Information Outlook, June 1997

Volume 1, Issue 6https://scholarworks.sjsu.edu/sla_io_1997/1005/thumbnail.jp

PF-OLA: A High-Performance Framework for Parallel On-Line Aggregation

Online aggregation provides estimates to the final result of a computation during the actual processing. The user can stop the computation as soon as the estimate is accurate enough, typically early in the execution. This allows for the interactive data exploration of the largest datasets. In this paper we introduce the first framework for parallel online aggregation in which the estimation virtually does not incur any overhead on top of the actual execution. We define a generic interface to express any estimation model that abstracts completely the execution details. We design a novel estimator specifically targeted at parallel online aggregation. When executed by the framework over a massive $8\text{TB}$ TPC-H instance, the estimator provides accurate confidence bounds early in the execution even when the cardinality of the final result is seven orders of magnitude smaller than the dataset size and without incurring overhead.Comment: 36 page

Synergies between Exoplanet Surveys and Variable Star Research

With the discovery of the first transiting extrasolar planetary system back to 1999, a great number of projects started to hunt for other similar systems. Because of the incidence rate of such systems was unknown and the length of the shallow transit events is only a few percent of the orbital period, the goal was to monitor continuously as many stars as possible for at least a period of a few months. Small aperture, large field of view automated telescope systems have been installed with a parallel development of new data reduction and analysis methods, leading to better than 1% per data point precision for thousands of stars. With the successful launch of the photometric satellites CoRot and Kepler, the precision increased further by one-two orders of magnitude. Millions of stars have been analyzed and searched for transits. In the history of variable star astronomy this is the biggest undertaking so far, resulting in photometric time series inventories immensely valuable for the whole field. In this review we briefly discuss the methods of data analysis that were inspired by the main science driver of these surveys and highlight some of the most interesting variable star results that impact the field of variable star astronomy.Comment: This is a review presented at "Wide-field variability surveys: a 21st-century perspective" - 22nd Los Alamos Stellar Pulsation Conference Series Meeting, held in: San Pedro de Atacama, Chile, Nov. 28-Dec. 2, 2016. To appear in Web of Conferences Journal: 13 pages, 8 figure

The Ambivalent Role of Mimetic Behaviors in Proximity Dynamics: Evidences on the French “Silicon Sentier”

This articles examines the peculiar role of mimetic behaviors in co-location processes. We start showing that geographical proximity between agents and/or firms is not a sufficient nor necessary condition for the collective performance of clusters. Other types of socio-economic proximities characterize clusters, and our purpose is to show that, among the several ways to analyze the complex links between proximities and clusters, the theoretical outlook on the role played by mimetic interactions in co-location processes are certainly one of the most promising. Mimetic behaviors of location (in economics and sociology) are introduced in order to demonstrate that co-location processes can be the result of sequentiality, uncertainty, legitimacy and non market interactions, rather than full rational and isolated decisions and pure strategic market interactions. According to the type of mimetic behavior at work in the clustering process, the nature of socio-economic proximity can differ and have a strong influence of the “evolutionary stability” of clusters. All these theoretical considerations are illustrated through the emblematic French case of “Silicon Sentier”, cluster which has gathered together three hundred firms of the French net-economy (the famous “dotcom”) during the Internet bubble swelling.cluster, mimetic interactions, proximity, stability, Silicon Sentier

Atmospheric Parameters and Metallicities for 2191 stars in the Globular Cluster M4

We report new metallicities for stars of Galactic globular cluster M4 using the largest number of stars ever observed at high spectral resolution in any cluster. We analyzed 7250 spectra for 2771 cluster stars gathered with the VLT FLAMES+GIRAFFE spectrograph at VLT. These medium resolution spectra cover by a small wavelength range, and often have very low signal-to-noise ratios. We attacked this dataset by reconsidering the whole method of abundance analysis of large stellar samples from beginning to end. We developed a new algorithm that automatically determines the atmospheric parameters of a star. Nearly all data preparation steps for spectroscopic analyses are processed on the syntheses, not the observed spectra. For 322 Red Giant Branch stars with $V \leq 14.7$ we obtain a nearly constant metallicity, $= -1.07$ ($\sigma$ = 0.02). No difference in the metallicity at the level of $0.01 ~\textrm{dex}$ is observed between the two RGB sequences identified by \cite{Monelli:2013us}. For 1869 Subgiant and Main Sequence Stars $V > 14.7$ we obtain $= -1.16$ ($\sigma$ = 0.09) after fixing the microturbulent velocity. These values are consistent with previous studies that have performed detailed analyses of brighter RGB stars at higher spectroscopic resolution and wavelength coverage. It is not clear if the small mean metallicity difference between brighter and fainter M4 members is real or is the result of the low signal-to-noise characteristics of the fainter stars. The strength of our approach is shown by recovering a metallicity close to a single value for more than two thousand stars, using a dataset that is non-optimal for atmospheric analyses. This technique is particularly suitable for noisy data taken in difficult observing conditions.Comment: 17 pages, 20 figures, 3 tables. Accepted for publication in The Astronomical Journa

Progressive Analytics: A Computation Paradigm for Exploratory Data Analysis

Exploring data requires a fast feedback loop from the analyst to the system, with a latency below about 10 seconds because of human cognitive limitations. When data becomes large or analysis becomes complex, sequential computations can no longer be completed in a few seconds and data exploration is severely hampered. This article describes a novel computation paradigm called Progressive Computation for Data Analysis or more concisely Progressive Analytics, that brings at the programming language level a low-latency guarantee by performing computations in a progressive fashion. Moving this progressive computation at the language level relieves the programmer of exploratory data analysis systems from implementing the whole analytics pipeline in a progressive way from scratch, streamlining the implementation of scalable exploratory data analysis systems. This article describes the new paradigm through a prototype implementation called ProgressiVis, and explains the requirements it implies through examples.Comment: 10 page