Discovering candidates for gene network expansion by distributed volunteer computing

Our group has recently developed gene@home, a BOINC project that permits to search for candidate genes for the expansion of a gene regulatory network using gene expression data. The gene@home project adopts intensive variable-subsetting strategies enabled by the computational power provided by the volunteers who have joined the project by means of the BOINC client. Our project exploits the PC algorithm (Spirtes and Glymour, 1991) in an iterative way, for discovering putative causal relationships within each subset of variables. This paper presents our infrastructure, called TN-Grid, that is hosting the gene@home project. Gene@home implements a novel method for Network Expansion by Subsetting and Ranking Aggregation (NESRA), producing a list of genes that are candidates for the gene network expansion task. NESRA is an algorithm that has: 1) a ranking procedure that systematically subsets the variables; the subsetting is iterated several times and a ranked list of candidates is produced by counting the number of times a relationship is found; 2) several ranking steps are executed with different values of the dimension of the subsets and with different number of iterations producing several ranked lists; 3) the ranked lists are aggregated by using a state-of-the-art ranking aggregator. In our experimental results, we show that NESRA outperforms both the PC algorithm and its order-independent version called PC*. Evaluations and experiments are done by means of the gene@home project on a real gene regulatory network of the model plant Arabidopsis thaliana

Strain-level microbial epidemiology and population genomics from shotgun metagenomics

Identifying microbial strains and characterizing their functional potential is essential for pathogen discovery, epidemiology and population genomics. We present pangenome-based phylogenomic analysis (PanPhlAn; http://segatalab.cibio.unitn.it/tools/panphlan), a tool that uses metagenomic data to achieve strain-level microbial profiling resolution. PanPhlAn recognized outbreak strains, produced the largest strain-level population genomic study of human-associated bacteria and, in combination with metatranscriptomics, profiled the transcriptional activity of strains in complex communities

Design of Sustainable Product Lifecycles

Generating sustainable product life cycles explains the importance of a holistic long-term planning and management approach to reaching a maximum product benefit over the entire life cycle. The paradigm of thinking in product life cycles supports manufacturers in shaping successful products. The book promotes various methods and tools for life cycle management and merges them into an integrated planning approach. In this monograph Europe’s leading academic experts in the field of life cycle management have consolidated their expertise. Readers will learn about different tools and methods for life cycle modelling and digital information support. Industrial examples show how a consistent product data management with closed-loop information cycles enables manufacturers to activate the hidden performance potentials of their products and in their production lines. In this respect Product life cycle design also illustrates the benefits of a networked production including integrated product service systems and innovative business models, and presents methods for evaluating the economic and ecological impacts of life cycle design, highlighting them with practical examples. The book addresses professionals as well as researchers and students from the field of life cycle management. Practitioners and researchers pursuing life cycle excellence will benefit from the comprehensive coverage of methods and various examples from industry

Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era

Manufacturers and service providers are called to design, plan, and operate globalised manufacturing networks, addressing to challenges of increasing complexity in all aspects of product and production life cycle. These factors, caused primarily by the increasing demand for product variety and shortened life cycles, generate a number of issues related to the life cycle of manufacturing systems and networks. Focusing on the aspects that affect manufacturing network performance, this work reviews the exiting literature around the design, planning, and control of manufacturing networks in the era of mass customisation and personalisation. The considered life cycle aspects include supplier selection, initial manufacturing network design, supply chain coordination, complexity, logistics management, inventory and capacity planning and management, lot sizing, enterprise resource planning, customer relationship management, and supply chain control. Based on this review and in correlation with the view of the manufacturing networks and facilities of the future, directions for the development of methods and tools to satisfy product-service customisation and personalisation are promoted

Managerial challenges of Industry 4.0: an empirically backed research agenda for a nascent field

The increasing intelligence of products and systems, their intra-company cross-linking and their cross-company integration into value creation networks is referred to as Industry 4.0. Academics and practitioners, largely agreeing on the global importance of this proclaimed industrial revolution, have published many contributions on the topic. Research, however, is rather focused on investigating single technologies in quite specific application domains and largely neglects the profound managerial challenges underlying Industry 4.0. Given the recent plea for a more active contribution from the management science community, we strive to establish Industry 4.0 as a challenging but promising field for management research, and aim to assist scholars in engaging with the topic. Therefore, we first gather and analyze extant contributions by means of a systematic literature review and synthesize the information gained into 18 managerial challenges of Industry 4.0 falling into six interrelated clusters: (1) strategy and analysis, (2) planning and implementation, (3) cooperation and networks, (4) business models, (5) human resources and (6) change and leadership. Considering that Industry 4.0 is still an emerging topic and publications may therefore not always be found in highly ranked journals, we aimed to increase the confidence in our findings and triangulated our data by conducting an online survey of industry experts and academics that allows us to qualify the identified challenges in terms of importance and future research need. On this basis, we present an empirically backed research agenda and suggest fruitful avenues for future research in three basic categories: practice-enhancing research, knowledge-enhancing research, and high-impact research