Policy Mixes for Industrial Transformation: Lessons from Finland and Sweden

An accelerated transition of the existing industry sectors towards low-carbon and renewable energy technologies is crucial to achieving global climate targets and national net zero emission commitments. This thesis departs from the notion that many governments increasingly emphasise the possibilities of combining such a transformation with domestic “green growth”. Recent research suggests that policymakers can influence innovation and transition processes through the implementation of transformative innovation policies, including a mix of instruments oriented towards climate and industrialisation goals. At the same time, scholars have stressed that the design and implementation of policy mixes play a key role in their effectiveness. Despite these advances, there is a lack of studies addressing the outcomes of such policy mixes in the context of transformative change in the industry.This licentiate thesis aims to enrich the current understanding of the impact of policy mixes on industrial transformation processes. To this end, this thesis builds on three historical case studies of industrial transformation in the Nordic countries. It combines qualitative interviews with secondary data and social network analysis to reconstruct how the implemented policy mixes have influenced the industrial transformation over an extended period (2003-2022). Theoretically, this thesis departs from the innovation systems approach and draws on insights from studies of transformative innovation policies, mission-oriented innovation systems and value chains.The thesis contributes to a more advanced understanding of the underlying processes by which policy mixes influence industrial processes towards the targeted transformative change. First, the thesis contributes with a typology of value chains, which describes and explains how differences in the type, design and implementation of policy mixes could lead to alternative value chain developments. Second, the thesis develops a process model that describes and explains how policy feedbacks affect the evolution of policy mixes and the subsequent emergence of renewable energy technologies and industrial structures. Third, the thesis contributes to the understanding of the impact of collaborative R&D programs directed toward promoting low-carbon innovation and experimentation in the established industry by investigating the role of the main Swedish industrial emitters in one policy-driven R&D network

Policy mixes and policy feedback: Implications for green industrial growth in the Swedish biofuels industry

Policymakers have increasingly voiced an ambition to combine the transition to a climate-neutral society with a “green” domestic industrial agenda. In recent years, innovation systems scholars have advanced the understanding of the evolution of industries around renewable energy technologies as well as the role of policy feedback (and indeed politics) surrounding the development of domestic green industrial development policies. To take a step towards combining these literature streams, the purpose of this paper is to investigate the role of policy mixes and policy feedback in the emergence of domestic green industries. This is achieved in the empirical case of biofuels in Sweden, and the findings show that policy feedback dynamics created difficulties in aligning the national policy mix with the technology and industrial developments in the country. The resulting political uncertainty predominantly hampered the scaling up of domestic production capacity, while R&D and import of biofuels instead could grow strong. Based on this empirical case, a process model is developed to explain the role of policy feedback in the development of domestic industries, thus demonstrating how the growth of domestic industries is driven by the interplay of policy effects and various feedback processes. The findings suggest that future research into the role of policies in “green” domestic industry growth should devote more attention to the dynamics driving the co-evolution of policy, technology and industry structures

Model-driven user interfaces for bioinformatics data resources: regenerating the wheel as an alternative to reinventing it

BACKGROUND: The proliferation of data repositories in bioinformatics has resulted in the development of numerous interfaces that allow scientists to browse, search and analyse the data that they contain. Interfaces typically support repository access by means of web pages, but other means are also used, such as desktop applications and command line tools. Interfaces often duplicate functionality amongst each other, and this implies that associated development activities are repeated in different laboratories. Interfaces developed by public laboratories are often created with limited developer resources. In such environments, reducing the time spent on creating user interfaces allows for a better deployment of resources for specialised tasks, such as data integration or analysis. Laboratories maintaining data resources are challenged to reconcile requirements for software that is reliable, functional and flexible with limitations on software development resources. RESULTS: This paper proposes a model-driven approach for the partial generation of user interfaces for searching and browsing bioinformatics data repositories. Inspired by the Model Driven Architecture (MDA) of the Object Management Group (OMG), we have developed a system that generates interfaces designed for use with bioinformatics resources. This approach helps laboratory domain experts decrease the amount of time they have to spend dealing with the repetitive aspects of user interface development. As a result, the amount of time they can spend on gathering requirements and helping develop specialised features increases. The resulting system is known as Pierre, and has been validated through its application to use cases in the life sciences, including the PEDRoDB proteomics database and the e-Fungi data warehouse. CONCLUSION: MDAs focus on generating software from models that describe aspects of service capabilities, and can be applied to support rapid development of repository interfaces in bioinformatics. The Pierre MDA is capable of supporting common database access requirements with a variety of auto-generated interfaces and across a variety of repositories. With Pierre, four kinds of interfaces are generated: web, stand-alone application, text-menu, and command line. The kinds of repositories with which Pierre interfaces have been used are relational, XML and object databases

A classification of tasks for the systematic study of immune response using functional genomics data

A full understanding of the immune system and its responses to infection by different pathogens is important for the development of anti-parasitic vaccines. A growing number of large-scale experimental techniques, such as microarrays, are being used to gain a better understanding of the immune system. To analyse the data generated by these experiments, methods such as clustering are widely used. However, individual applications of these methods tend to analyse the experimental data without taking publicly available biological and immunological knowledge into account systematically and in an unbiased manner. To make best use of the experimental investment, to benefit from existing evidence, and to support the findings in the experimental data, available biological information should be included in the analysis in a systematic manner. In this review we present a classification of tasks that shows how experimental data produced by studies of the immune system can be placed in a broader biological context. Taking into account available evidence, the classification can be used to identify different ways of analysing the experimental data systematically. We have used the classification to identify alternative ways of analysing microarray data, and illustrate its application using studies of immune responses in mice to infection with the intestinal nematode parasites Trichuris muris and Heligmosomoides polygyrus

e-Fungi: a data resource for comparative analysis of fungal genomes.

BACKGROUND: The number of sequenced fungal genomes is ever increasing, with about 200 genomes already fully sequenced or in progress. Only a small percentage of those genomes have been comprehensively studied, for example using techniques from functional genomics. Comparative analysis has proven to be a useful strategy for enhancing our understanding of evolutionary biology and of the less well understood genomes. However, the data required for these analyses tends to be distributed in various heterogeneous data sources, making systematic comparative studies a cumbersome task. Furthermore, comparative analyses benefit from close integration of derived data sets that cluster genes or organisms in a way that eases the expression of requests that clarify points of similarity or difference between species. DESCRIPTION: To support systematic comparative analyses of fungal genomes we have developed the e-Fungi database, which integrates a variety of data for more than 30 fungal genomes. Publicly available genome data, functional annotations, and pathway information has been integrated into a single data repository and complemented with results of comparative analyses, such as MCL and OrthoMCL cluster analysis, and predictions of signaling proteins and the sub-cellular localisation of proteins. To access the data, a library of analysis tasks is available through a web interface. The analysis tasks are motivated by recent comparative genomics studies, and aim to support the study of evolutionary biology as well as community efforts for improving the annotation of genomes. Web services for each query are also available, enabling the tasks to be incorporated into workflows. CONCLUSION: The e-Fungi database provides fungal biologists with a resource for comparative studies of a large range of fungal genomes. Its analysis library supports the comparative study of genome data, functional annotation, and results of large scale analyses over all the genomes stored in the database. The database is accessible at http://www.e-fungi.org.uk, as is the WSDL for the web services.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

The Comprehensive Phytopathogen Genomics Resource: a web-based resource for data-mining plant pathogen genomes

The Comprehensive Phytopathogen Genomics Resource (CPGR) provides a web-based portal for plant pathologists and diagnosticians to view the genome and trancriptome sequence status of 806 bacterial, fungal, oomycete, nematode, viral and viroid plant pathogens. Tools are available to search and analyze annotated genome sequences of 74 bacterial, fungal and oomycete pathogens. Oomycete and fungal genomes are obtained directly from GenBank, whereas bacterial genome sequences are downloaded from the A Systematic Annotation Package (ASAP) database that provides curation of genomes using comparative approaches. Curated lists of bacterial genes relevant to pathogenicity and avirulence are also provided. The Plant Pathogen Transcript Assemblies Database provides annotated assemblies of the transcribed regions of 82 eukaryotic genomes from publicly available single pass Expressed Sequence Tags. Data-mining tools are provided along with tools to create candidate diagnostic markers, an emerging use for genomic sequence data in plant pathology. The Plant Pathogen Ribosomal DNA (rDNA) database is a resource for pathogens that lack genome or transcriptome data sets and contains 131 755 rDNA sequences from GenBank for 17 613 species identified as plant pathogens and related genera

Comparative Genome Analysis of Filamentous Fungi Reveals Gene Family Expansions Associated with Fungal Pathogenesis

Fungi and oomycetes are the causal agents of many of the most serious diseases of plants. Here we report a detailed comparative analysis of the genome sequences of thirty-six species of fungi and oomycetes, including seven plant pathogenic species, that aims to explore the common genetic features associated with plant disease-causing species. The predicted translational products of each genome have been clustered into groups of potential orthologues using Markov Chain Clustering and the data integrated into the e-Fungi object-oriented data warehouse (http://www.e-fungi.org.uk/). Analysis of the species distribution of members of these clusters has identified proteins that are specific to filamentous fungal species and a group of proteins found only in plant pathogens. By comparing the gene inventories of filamentous, ascomycetous phytopathogenic and free-living species of fungi, we have identified a set of gene families that appear to have expanded during the evolution of phytopathogens and may therefore serve important roles in plant disease. We have also characterised the predicted set of secreted proteins encoded by each genome and identified a set of protein families which are significantly over-represented in the secretomes of plant pathogenic fungi, including putative effector proteins that might perturb host cell biology during plant infection. The results demonstrate the potential of comparative genome analysis for exploring the evolution of eukaryotic microbial pathogenesis

Comparative metagenomics approaches to characterize the soil fungal communities of western coastal region, Saudi Arabia

A total of 145007 reads were obtained from pyrosequencing for all the 4 samples. The total count ranged from 11,301,014 (Mecca old road) to 23,503,512 bp (Thuwal). A total of 460 fungal species belonging to 133 genera, 58 families, 33 orders, 13 classes and 4 phyla was identified across the four sites. The most abundant phylum at all four sites was Ascomycota followed by Basidiomycota. Four phyla (Ascomycota-99.31%, Basidiomycota-0.59%, Chytridiomycota-0.04%, Glomeromycota-0.03%) were detected in Khulais. Except for Glomeromycota, all phyla were detected at Mecca old road (Ascomycota-74.26%, Basidiomycota-25.71%, Chytridiomycota-0.01%) and Thuwal (Ascomycota-99.59%, Basidiomycota-0.40%, Chytridiomycota-0.002%); while only Ascomycota-90.98% and Basidiomycota-9.01% were detected in Asfan road. At the class level, Sordariomycetes was predominantly observed at Asfan road-59.88%, Khulais-68.26% and Thuwal-94.84%; while Pezizomycetes was dominant at Mecca old road-56.01%, was absent at Asfan road. Agaricomycetes was present only at Mecca old road-25.73%; while Tremellomycetes-5.77%, Malasseizomycetes-2.13% and Microbotryomycetes-1.10% were found only at Asfan road. The phylogenetic trees revealed that clear genus level differences are visible across all the four sites, with an overall predominance of Thielavia followed by Madurella, Aspergillus, and Gelasinospora. Chaetomium sp., Aspergillus caespitosus and Aspergillus sp. were found in moderate (Mecca old road and Thuwal) to abundant (Asfan road and Khulais) quantities. Thielavia sp., Thielavia hyalocarpa and Madurella sp. are found in moderate quantities at Khulais and Mecca old road, while in abundant levels at Asfan road and Thuwal. Fusarium equisati and F. oxysporum were detected at Thuwal and Khulais. Sordaria araneosa was present at Khulais, while Malasseiza globosa species was detected in moderate quantities across all sites except Khulais