A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Small State Cultures of Consensus : State Traditions and Consensus-Seeking in the Neo-Corporatist and Neutrality Policies in Post-1945 Austria and Finland

Austria and Finland are persistently referred to as the “success stories” of post-1945 European history. Notwithstanding their different points of departure, in the course of the Cold War both countries portrayed themselves as small and neutral border-states in the world dictated by superpower politics. By the 1970s, both countries frequently ranked at the top end in various international classifications regarding economic development and well-being in society. This trend continues today. The study takes under scrutiny the concept of consensus which figures centrally in the two national narratives of post-1945 success. Given that the two domestic contexts as such only share few direct links with one another and are more obviously different than similar in terms of their geographical location, historical experiences and politico-cultural traditions, the analogies and variations in the anatomies of the post-1945 “cultures of consensus” provide an interesting topic for a historical comparative and cross-national examination. The main research question concerns the identification and analysis of the conceptual and procedural convergence points of the concepts of the state and consensus. The thesis is divided into six main chapters. After the introduction, the second chapter presents the theoretical framework in more detail by focusing on the key concepts of the study – the state and consensus. Chapter two also introduces the comparative historical and cross-national research angles. Chapter three grounds the key concepts of the state and consensus in the historical contexts of Austria and Finland by discussing the state, the nation and democracy in a longer term comparative perspective. The fourth and fifth chapter present case studies on the two policy fields, the “pillars”, upon which the post-1945 Austrian and Finnish cultures of consensus are argued to have rested. Chapter four deals with neo-corporatist features in the economic policy making and chapter five discusses the building up of domestic consensus regarding the key concepts of neutrality policies in the 1950s and 1960s. The study concludes that it was not consensus as such but the strikingly intense preoccupation with the theme of domestic consensus that cross-cut, in a curiously analogous manner, the policy-making processes studied. The main challenge for the post-1945 architects of Austrian and Finnish cultures of consensus was to find strategies and concepts for consensus-building which would be compatible with the principles of democracy. Discussed at the level of procedures, the most important finding of the study concerns the triangular mechanism of coordination, consultation and cooperation that set into motion and facilitated a new type of search for consensus in both post-war societies. In this triangle, the agency of the state was central, though in varying ways. The new conceptions concerning a small state’s position in the Cold War world also prompted cross-nationally perceivable willingness to reconsider inherited concepts and procedures of the state and the nation. At the same time, the ways of understanding the role of the state and its relation to society remained profoundly different in Austria and Finland and this basic difference was in many ways reflected in the concepts and procedures deployed in the search for consensus and management of domestic conflicts. For more detailed information, please consult the author.

"Hey world, take a look at me!": Appreciating the human body on social network sites

Social network sites (SNSs) such as Facebook have the potential to persuade people to adopt a lifestyle based on exercise and healthy nutrition. We report the findings of a qualitative study of an SNS for bodybuilders, looking at how bodybuilders present themselves online and how they orchestrate the SNS with their offline activities. Discussing the persuasive element of appreciation, we aim to extend previous work on persuasion in web 2.0 technologies.

The emerging world of small ORFs

Small open reading frames (sORFs) are an often overlooked feature of plant genomes. Initially found in plant viral RNAs and considered an interesting curiosity, an increasing number of these sORFs have been shown to encode functional peptides or play a regulatory role. The recent discovery that many of these sORFs initiate with start codons other than AUG, together with the identification of functional small peptides encoded in supposedly noncoding primary miRNA transcripts (pri-miRs), has drastically increased the number of potentially functional sORFs within the genome. Here we review how advances in technology, notably ribosome profiling (RP) assays, are complementing bioinformatics and proteogenomic methods to provide powerful ways to identify these elusive features of plant genomes, and highlight the regulatory roles sORFs can play.

Network-error correcting codes using small fields

Recently, Ebrahimi and Fragouli proposed an algorithm to construct scalar network codes using small fields (and vector network codes of small lengths) satisfying multicast constraints in a given single-source, acyclic network. The contribution of this paper is two fold. Primarily, we extend the scalar network coding algorithm of Ebrahimi and Fragouli (henceforth referred to as the EF algorithm) to block network-error correction. Existing construction algorithms of block network-error correcting codes require a rather large field size, which grows with the size of the network and the number of sinks, and thereby can be prohibitive in large networks. We give an algorithm which, starting from a given network-error correcting code, can obtain another network code using a small field, with the same error correcting capability as the original code. Our secondary contribution is to improve the EF Algorithm itself. The major step in the EF algorithm is to find a least degree irreducible polynomial which is coprime to another large degree polynomial. We suggest an alternate method to compute this coprime polynomial, which is faster than the brute force method in the work of Ebrahimi and Fragouli.

Ultra-small sulphur nanoparticles configured inside a flexible organic mixed conducting network as a cathode for lithium-sulphur batteries

The major challenges in Li-S batteries are the formation of soluble polysulphides during the reversible conversion of S-8 <-> Li2S, large changes in sulphur particle volume during lithiation and extremely poor charge transport in sulphur. We demonstrate here a novel and simple strategy to overcome these challenges towards practical realization of a stable high performance Li-S battery. For the first time, a strategy is developed which does away with the necessity of pre-fabricated high surface area hollow-structured adsorbates and also multiple nontrivial synthesis steps related to sulphur loading inside such adsorbates. A lithiated polyethylene glycol (PEG) based surfactant tethered on ultra-small sulphur nanoparticles and wrapped up with polyaniline (PAni) (abbreviated as S-MIEC) is demonstrated here as an exceptional cathode for Li-S batteries. The PEG and PAni network around the sulphur nanoparticles serves as an efficient flexible trap for sulphur and polysulphides and also provides distinct pathways for electrons (through PAni) and ions (through PEG) during battery operation. Contrary to the cathodes demonstrated based on various carbon-sulphur composites, the mixed conducting S-MIEC showed an extremely high loading of 75%. The S-MIEC exhibited a stable capacity of nearly 900 mA h g(-1) at the end of 100 cycles at a 1C current rate.

Approaches and frameworks for management and research in small-scale fisheries in the developing world

Commonly adopted approaches to managing small-scale fisheries (SSFs) in developing countries do not ensure sustainability. Progress is impeded by a gap between innovative SSF research and slower-moving SSF management. The paper aims to bridge the gap by showing that the three primary bases of SSF management--ecosystem, stakeholders’ rights and resilience--are mutually consistent and complementary. It nominates the ecosystem approach as an appropriate starting point because it is established in national and international law and policy. Within this approach, the emerging resilience perspective and associated concepts of adaptive management and institutional learning can move management beyond traditional control and resource-use optimization, which largely ignore the different expectations of stakeholders; the complexity of ecosystem dynamics; and how ecological, social, political and economic subsystems are linked. Integrating a rights-based perspective helps balance the ecological bias of ecosystem-based and resilience approaches. The paper introduces three management implementation frameworks that can lend structure and order to research and management regardless of the management approach chosen. Finally, it outlines possible research approaches to overcome the heretofore limited capacity of fishery research to integrate across ecological, social and economic dimensions and so better serve the management objective of avoiding fishery failure by nurturing and preserving the ecological, social and institutional attributes that enable it to renew and reorganize itself. (PDF contains 29 pages)

Production and conservation of nutrient-rich small fish (SIS) in ponds and wetlands for nutrition security and livelihoods in South Asia: Proceedings of a World Bank/SAFANSI funded regional workshop on small fish and nutrition, Dhaka, Bangladesh, 1st - 2nd March 2014

Small indigenous fish species (SIS) are an important source of essential macro- and micronutrients that can play an important role in the elimination of malnutrition and micronutrient deficiencies in the populations of many South and Southeast Asian countries. Of the 260 freshwater fish species in Bangladesh, more than 140 are classified as SIS and are an integral part of the rural Bangladeshi diet. As many SIS are eaten whole, with organs and bones, they contain high amounts of vitamins and minerals, including calcium, and iron and zinc. Some SIS, such as mola, are also rich in vitamin A. SIS are often cooked with vegetables and a little oil, so they contribute to the food diversity of the rural poor.SIS are recognized as a major animal-source food group, contributing to improved food and nutrition security and livelihoods of the people of South and Southeast Asia. The purpose of this workshop is to bring together policy makers, extension agents, researchers, non-governmental and development organizations to share knowledge about small fish, their contribution to better nutrition, production technologies, and strategies for wider dissemination of pond culture and wetland based-production and conservation technologies. The workshop is expected to generate ideas for further research and development of sustainable technologies for production, management and conservation of SIS for the benefit of the people of Bangladesh as well as the South and Southeast Asian region.

Small but influential: the role of microRNAs on gene regulatory network and 3 ' UTR evolution

MicroRNAs (miRNAs) are endogenous similar to 22 nucleotide noncoding RNAs that regulate the expression of complementary messenger RNAs (mRNAs). Thousands of miRNA genes have been found in diverse species, and many of them are highly conserved. With the mi

A System for Representing and Using Real-World Knowledge

This report describes a knowledge-base system in which the information is stored in a network of small parallel processing elements ??de and link units ??ich are controlled by an external serial computer. This network is similar to the semantic network system of Quillian, but is much more tightly controlled. Such a network can perform certain critical deductions and searches very quickly; it avoids many of the problems of current systems, which must use complex heuristics to limit and guided their searches. It is argued (with examples) that the key operation in a knowledge-base system is the intersection of large explicit and semi-explicit sets. The parallel network system does this in a small, essentially constant number of cycles; a serial machine takes time proportional to the size of the sets, except in special cases.

Demand-based Document Dissemination for the World-Wide Web

We analyzed the logs of our departmental HTTP server http://cs-www.bu.edu as well as the logs of the more popular Rolling Stones HTTP server http://www.stones.com. These servers have very different purposes; the former caters primarily to local clients, whereas the latter caters exclusively to remote clients all over the world. In both cases, our analysis showed that remote HTTP accesses were confined to a very small subset of documents. Using a validated analytical model of server popularity and file access profiles, we show that by disseminating the most popular documents on servers (proxies) closer to the clients, network traffic could be reduced considerably, while server loads are balanced. We argue that this process could be generalized so as to provide for an automated demand-based duplication of documents. We believe that such server-based information dissemination protocols will be more effective at reducing both network bandwidth and document retrieval times than client-based caching protocols [2].

Measuring the Behavior of a World-Wide Web Server

Server performance has become a crucial issue for improving the overall performance of the World-Wide Web. This paper describes Webmonitor, a tool for evaluating and understanding server performance, and presents new results for a realistic workload. Webmonitor measures activity and resource consumption, both within the kernel and in HTTP processes running in user space. Webmonitor is implemented using an efficient combination of sampling and event-driven techniques that exhibit low overhead. Our initial implementation is for the Apache World-Wide Web server running on the Linux operating system. We demonstrate the utility of Webmonitor by measuring and understanding the performance of a Pentium-based PC acting as a dedicated WWW server. Our workload uses a file size distribution with a heavy tail. This captures the fact that Web servers must concurrently handle some requests for large audio and video files, and a large number of requests for small documents, containing text or images. Our results show that in a Web server saturated by client requests, over 90% of the time spent handling HTTP requests is spent in the kernel. Furthermore, keeping TCP connections open, as required by TCP, causes a factor of 2-9 increase in the elapsed time required to service an HTTP request. Data gathered from Webmonitor provide insight into the causes of this performance penalty. Specifically, we observe a significant increase in resource consumption along three dimensions: the number of HTTP processes running at the same time, CPU utilization, and memory utilization. These results emphasize the important role of operating system and network protocol implementation in determining Web server performance.

A Neural Network Architecture for Autonomous Learning, Recognition, and Prediction in a Nonstationary World

In a constantly changing world, humans are adapted to alternate routinely between attending to familiar objects and testing hypotheses about novel ones. We can rapidly learn to recognize and narne novel objects without unselectively disrupting our memories of familiar ones. We can notice fine details that differentiate nearly identical objects and generalize across broad classes of dissimilar objects. This chapter describes a class of self-organizing neural network architectures--called ARTMAP-- that are capable of fast, yet stable, on-line recognition learning, hypothesis testing, and naming in response to an arbitrary stream of input patterns (Carpenter, Grossberg, Markuzon, Reynolds, and Rosen, 1992; Carpenter, Grossberg, and Reynolds, 1991). The intrinsic stability of ARTMAP allows the system to learn incrementally for an unlimited period of time. System stability properties can be traced to the structure of its learned memories, which encode clusters of attended features into its recognition categories, rather than slow averages of category inputs. The level of detail in the learned attentional focus is determined moment-by-moment, depending on predictive success: an error due to over-generalization automatically focuses attention on additional input details enough of which are learned in a new recognition category so that the predictive error will not be repeated. An ARTMAP system creates an evolving map between a variable number of learned categories that compress one feature space (e.g., visual features) to learned categories of another feature space (e.g., auditory features). Input vectors can be either binary or analog. Computational properties of the networks enable them to perform significantly better in benchmark studies than alternative machine learning, genetic algorithm, or neural network models. Some of the critical problems that challenge and constrain any such autonomous learning system will next be illustrated. Design principles that work together to solve these problems are then outlined. These principles are realized in the ARTMAP architecture, which is specified as an algorithm. Finally, ARTMAP dynamics are illustrated by means of a series of benchmark simulations.