Graphical Models

"Networks are mathematically directed (in practical applications also undirected) graphs and a graph is a one-dimensional abstract complex, i.e., a topological space. Network theory focuses on various topological structures and properties, dynamic properties, and functionality-topology relationship, etc. There are some common mathematical foundations, theories and methodology for network analysis, in which graph theory, statistics, and operational research, etc., are the fundamental sciences of network analysis. Various emerging biological networks, at both micro- and macro- levels, will provide numerous sources for the development of general network theory and methodology and also facilitate the development of theory and methodology of biological networks.

Biological network analysis is a fast moving science. Many core scientific issues, for example, ecological structure, co-evolution, co-extinction and biodiversity conservation in ecology, and cancer development and metabolic regulation in health science, etc., are expected to be addressed by network approaches and network analysis. Network analysis is becoming the core methodology to treat complex biological systems. As the fast development of this area, more and more papers on biological networks are published.

At present explosive numbers of quality papers on biological networks are being published each year. The initiation of the journal, Network Biology, will provide a public and unified platform for the publication of these studies. From this integrated and unique journal, researchers, university teachers and students will thoroughly have an in-depth and complete insight on knowledge, methodology and recent advances of biological networks.

In the view of system dynamics, biological networks are always self-organized systems with emergent, autonomous and adaptive properties. Their dynamics can be represented by agent-based modeling, individual-based modeling and some other methodologies like neural network modeling. Therefore, agent-based modeling, individual-based modeling, self-organization of biological systems, and neural network modeling, etc., fall into the aims and scope of the journal, Network Biology.

The NETWORK BIOLOGY (ISSN 2220-8879) is an open access, peer-reviewed online journal that considers scientific articles in all different areas of network biology. It is the transactions of the International Society of Network Biology.It dedicates to the latest advances in network biology. The goal of this journal is to keep a record of the state-of-the-art research and promote the research work in these fast moving areas. The topics to be covered by Network Biology include, but are not limited to:

•Theories, algorithms and programs of network analysis
•Innovations and applications of biological networks
•Dynamics, optimization and control of biological networks
•Ecological networks, food webs and natural equilibrium
•Co-evolution, co-extinction, biodiversity conservation
•Metabolic networks, protein-protein interaction networks, biochemical reaction networks, gene networks, transcriptional regulatory networks, cell cycle networks, phylogenetic networks, network motifs
•Physiological networks
•Network regulation of metabolic processes, human diseases and ecological systems
•Social networks, epidemiological networks
•System complexity, self-organized systems, emergence of biological systems, agent-based modeling, individual-based modeling, neural network modeling, and other network-based modeling, etc.
We are also interested in short communications that clearly address a specific issue or completely present a new ecological network, food web, or metabolic or gene network, etc.

Authors can submit their works to the email box of this journal, networkbiology@iaees.org. All manuscripts submitted to this journal must be previously unpublished and may not be considered for publication elsewhere at any time during review period of this journal. Authors are asked to read Author Guidelines before submitting manuscripts.

In addition to free submissions from authors around the world, special issues are also accepted. The organizer of a special issue can collect submissions (yielded from a research project, a research group, etc.) on a specific research topic, or submissions of a scientific conference for publication of special issue.

Network Biology 
ISSN 2220-8879
URL: http://www.iaees.org/publications/journals/nb/online-version.asp
RSS feed: http://www.iaees.org/publications/journals/nb/rss.xml
E-mail: networkbiology@iaees.org
Editor-in-Chief: WenJun Zhang"

The Walden 7  building is presented as a rara avis on the Spanish housing scene of the 1970s. The Taller de Arquitectura team uses the model as a fun- damental graphic tool throughout the entire project process, in order to develop the proposal of this unique building.
We will check how the chameleonic character of the model will define each phase of the project, with a different model capable of narrating in a different way each phase - work, structure or dioramas models, building the Walden 7 on a small scale. Therefore, the models are an intangible graphic heritage that shows us the project process, allowing us to reread the finished building from a new point of view.

Resumen En esta contribución se describen una serie de herramientas visuales útiles en la inspección de patrones de diversidad para comunidades ecológicas. Para cada método, se expone la forma de construcción y ventajas y principios de aplicación para datos de peces estuarino-lagunares. Se incluye una breve reflexión sobre la aplicabilidad e impacto de estos métodos en la toma de decisiones sobre el conocimiento y conservación de las comunidades ecológicas.

In this project I construct a statistical procedure to infer a biological network of very high dimensionality, where microRNAs, small RNAs, are supposed to down-regulate mRNAs, also called target genes. From a statistical point of view, I address this problem by building a network that represents the biological regulatory system, indicating which microRNA regulates which gene. In particular, this method provides a novel graphical modeling approach that includes constraints on the regression coefficients to take into account the down-regulatory effect of the network. This approach is able to select single connections in the network, unlike previous methods in the Bayesian variable selection literature, which only allow the selection of covariates (microRNAs) that affect either all the genes or none of them. The main challenge of this project is represented by the dimensionality of the data. The stochastic search variable selection algorithm is able to efficiently explore the space of all possible networks and to find, for each gene, which microRNAs have high posterior probability of being down-regulating the gene. To help the selection, I also propose a new prior formulation which is able to integrate different sources of data, by exploiting information from sequence and structure analyses. Because many sources of information are integrated, the model is also able to determine which information is consistent with the data via posterior inference on the parameters defined in the data integration prior. The proposed method is general and can be easily applied to other types of network inference by integrating multiple data sources.

In order to effectively use technology in education, appropriate conceptual understandings are needed to guide the integration process. Today, there is a wide range of conceptual models that are developed and used in research and/or practice focusing on educational technology integration. Conceptual models are of relevance as they can bridge theory with practical applications. Today, there are a wide range of conceptual models are developed and used in research and/or practice focusing on educational technology integration. These models can be seen as simplified versions of theories for practical application or as condensed wisdoms of practice that need to be further investigated theoretically and empirically. However, there is insufficient agreement on the dimensions and criteria used to judge the quality of conceptual models in educational technology. Therefore, the main goals of this article are to: (1) develop criteria to assess the quality and scope of conceptual models and (2) identify and compare exemplary models for technology integration in educational settings along with these quality criteria. The resulting five criteria from this investigation provide the means to effectively evaluate the quality and scope of conceptual models focused on technology integration while providing additional insight into applying these models in research and practice.

The purpose of this paper is to formulate guidelines of analysis between the miguel Aguinaga building and its urban surrounding, in order to look into the design thinking strategies of the architect through some of the most representative buildings of his professional trajectory within the framework
of office buildings typology. The state of the art and text structure illustrate two parts. The first one makes reference to two topics: bibliographic review on modern Architecture´s consolidation in the city of medellin, and the use of architecture formal analysis categories on: emplacement, program, and
sections; the second one develops the formal analysis of the building in its original state through planimetrics and photographies of the times. These two parts intersect each other as a conclusion, where the building is presented
as a formal strategy of connection between the inside and the outside.

Symbols represent by codes like conventions, whereas icons represent by similarity (Couturat 1901; Dascal 1978; Gensini 1991; Serfati 2001). Until recently, much of the literature in philosophy of notation tended to follow Leibniz in assuming that we always or most often think in symbols. However, current debates have increasingly been driven by the recognition that any system of representation depends, to some extent, on iconicity, such that the purported line of demarcation is rather a continuum (Stjernfelt 2014). This slow but resolute turn toward iconic signs has begun to change how we see logic. With different emphases, linguists (Simone 1995; Van Langendonck 2007), logicians (Burch 1991; Shin 1994, 2002; Hammer 1995; Allein & Barwise 1996; Pietarinen 2006, 2010, 2011, 2012), historians of mathematics (Nets 2004; Mancosu, Jorgensen & Pedersen 2005; Giaquinto 2007), semioticians (Stjernfelt 2007, 2014; Bordron 2011; Dondero & Fontanille 2012), philosophers of mind (Champagne 2014) and cognitive scientists (Glasgow, Nara y Anan & Chandrasekaran 1995; Hoffmann 2010a, 2010b, 2011; Magnani 2011; Nakatsu 2010) have all recognized that a better understanding of reasoning by icons, specifically diagrams, is crucial to understanding problem-solving, inference-drawing, and hypothesis-making. Arguably, no one has explored the potential of iconic notations more systematically than C. S. Peirce. It is commonly believed that the birth of new formal logic(s) by Frege (1884), Russell (1903) and Couturat (1904) rendered Kant’s appeal to intuition redundant (cf. Kneale & Kneale 1962, VII-VIII; Coffa 1991; Carson & Huber 2006). However, an alternate line of development is clearly discernable in the work of Peirce. For Peirce, the notion of intuition is by no means redundant, being instead the faculty which allows necessary reasoning to yield informative truths (Peirce 1931-1958; Peirce 2010; cf. Hintikka 1980; Hookway 1985; Ketner 1985; Shin 1997; Pietarinen 2006; Stjernfelt 2007; Bellucci 2012). The diagram, in this Peircean paradigm, transforms intuition into a visual commodity amenable to careful public scrutiny. Indeed, one of the most striking features of Peirce’s diagrammatic notation is its depiction of inferences as transformations. Inference rules, being answerable to the self-same nature of images, are motivated in a way that makes them less rule-like. For example, enclosures, a common device used by Peirce, place distinct limits on what counts as included/inside, excluded/outside, or both. One can attempt to transgress these limits, but the iconic sign-vehicles at hand simply repel erroneous interpretations. While Venn exploited this to prove categorical syllogisms, Peirce shows how to generalize the method, thereby giving a novel justification for the normative force of logic. Peirce’s unpublished technical work in logic has thus far influenced debates mainly through the intermediary of specialists (Shin 2002; Sowa 2011), but the upcoming publication of Peirce’s full Existential Graphs (Logic of the Future, edited by A.-V. Pietarinen) promises to augment this rate of influence, by making available a 1000-page buffet of diagrammatic and iconic logical systems. Participants to this symposium are thus invited to reflect on how Peirce-inspired diagrammatic approaches to notation can positively reshape issues pertaining to logic, cognition, and reason-giving practices generally.