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Methods, software and technology

Section edited by Nitin Baliga and Pedro Mendes

This section covers the development and refinement of novel computational, statistical and experimental methods for the analysis of biological systems.

Page 4 of 5

  1. The KEGG PATHWAY database provides a plethora of pathways for a diversity of organisms. All pathway components are directly linked to other KEGG databases, such as KEGG COMPOUND or KEGG REACTION. Therefore, th...

    Authors: Clemens Wrzodek, Finja Büchel, Manuel Ruff, Andreas Dräger and Andreas Zell
    Citation: BMC Systems Biology 2013 7:15
  2. High-throughput (omic) data have become more widespread in both quantity and frequency of use, thanks to technological advances, lower costs and higher precision. Consequently, computational scientists are con...

    Authors: Yuanhua Liu, Valentina Devescovi, Suning Chen and Christine Nardini
    Citation: BMC Systems Biology 2013 7:14
  3. Many mathematical models characterizing mechanisms of cell fate decisions have been constructed recently. Their further study may be impossible without development of methods of model composition, which is com...

    Authors: Elena Kutumova, Andrei Zinovyev, Ruslan Sharipov and Fedor Kolpakov
    Citation: BMC Systems Biology 2013 7:13
  4. Signaling networks in eukaryotes are made up of upstream and downstream subnetworks. The upstream subnetwork contains the intertwined network of signaling pathways, while the downstream regulatory part contain...

    Authors: Dávid Fazekas, Mihály Koltai, Dénes Türei, Dezső Módos, Máté Pálfy, Zoltán Dúl, Lilian Zsákai, Máté Szalay-Bekő, Katalin Lenti, Illés J Farkas, Tibor Vellai, Péter Csermely and Tamás Korcsmáros
    Citation: BMC Systems Biology 2013 7:7
  5. Inference of gene-regulatory networks (GRNs) is important for understanding behaviour and potential treatment of biological systems. Knowledge about GRNs gained from transcriptome analysis can be increased by ...

    Authors: Michael Weber, Sebastian G Henkel, Sebastian Vlaic, Reinhard Guthke, Everardus J van Zoelen and Dominik Driesch
    Citation: BMC Systems Biology 2013 7:1
  6. Changes in environmental conditions require temporal effectuation of different metabolic pathways in order to maintain the organisms’ viability but also to enable the settling into newly arising conditions. Wh...

    Authors: Nadine Töpfer, Szymon Jozefczuk and Zoran Nikoloski
    Citation: BMC Systems Biology 2012 6:148
  7. Inferring the structure of gene regulatory networks (GRN) from a collection of gene expression data has many potential applications, from the elucidation of complex biological processes to the identification o...

    Authors: Anne-Claire Haury, Fantine Mordelet, Paola Vera-Licona and Jean-Philippe Vert
    Citation: BMC Systems Biology 2012 6:145
  8. With increased experimental availability and accuracy of bio-molecular networks, tools for their comparative and evolutionary analysis are needed. A key component for such studies is the alignment of networks.

    Authors: Michal Kolář, Jörn Meier, Ville Mustonen, Michael Lässig and Johannes Berg
    Citation: BMC Systems Biology 2012 6:144
  9. An efficient and reliable parameter estimation method is essential for the creation of biological models using ordinary differential equation (ODE). Most of the existing estimation methods involve finding the ...

    Authors: Gengjie Jia, Gregory Stephanopoulos and Rudiyanto Gunawan
    Citation: BMC Systems Biology 2012 6:142
  10. Experimental datasets are becoming larger and increasingly complex, spanning different data domains, thereby expanding the requirements for respective tool support for their analysis. Networks provide a basis ...

    Authors: Hendrik Rohn, Astrid Junker, Anja Hartmann, Eva Grafahrend-Belau, Hendrik Treutler, Matthias Klapperstück, Tobias Czauderna, Christian Klukas and Falk Schreiber
    Citation: BMC Systems Biology 2012 6:139
  11. Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situatio...

    Authors: Camille Terfve, Thomas Cokelaer, David Henriques, Aidan MacNamara, Emanuel Goncalves, Melody K Morris, Martijn van Iersel, Douglas A Lauffenburger and Julio Saez-Rodriguez
    Citation: BMC Systems Biology 2012 6:133
  12. Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated ...

    Authors: Nishanth Chemmangattuvalappil, Keith Task and Ipsita Banerjee
    Citation: BMC Systems Biology 2012 6:119
  13. Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations....

    Authors: Gautier Stoll, Eric Viara, Emmanuel Barillot and Laurence Calzone
    Citation: BMC Systems Biology 2012 6:116
  14. Mathematical/computational models are needed to understand cell signaling networks, which are complex. Signaling proteins contain multiple functional components and multiple sites of post-translational modific...

    Authors: Matthew S Creamer, Edward C Stites, Meraj Aziz, James A Cahill, Chin Wee Tan, Michael E Berens, Haiyong Han, Kimberley J Bussey, Daniel D Von Hoff, William S Hlavacek and Richard G Posner
    Citation: BMC Systems Biology 2012 6:107
  15. In order to reduce time and efforts to develop microbial strains with better capability of producing desired bioproducts, genome-scale metabolic simulations have proven useful in identifying gene knockout and ...

    Authors: Jong Myoung Park, Hye Min Park, Won Jun Kim, Hyun Uk Kim, Tae Yong Kim and Sang Yup Lee
    Citation: BMC Systems Biology 2012 6:106
  16. Modeling dynamic regulatory networks is a major challenge since much of the protein-DNA interaction data available is static. The Dynamic Regulatory Events Miner (DREM) uses a Hidden Markov Model-based approac...

    Authors: Marcel H Schulz, William E Devanny, Anthony Gitter, Shan Zhong, Jason Ernst and Ziv Bar-Joseph
    Citation: BMC Systems Biology 2012 6:104
  17. Transcription factor knockout microarrays (TFKMs) provide useful information about gene regulation. By using statistical methods for detecting differentially expressed genes between the gene expression microar...

    Authors: Tzu-Hsien Yang and Wei-Sheng Wu
    Citation: BMC Systems Biology 2012 6:102
  18. Inference about regulatory networks from high-throughput genomics data is of great interest in systems biology. We present a Bayesian approach to infer gene regulatory networks from time series expression data...

    Authors: Kenneth Lo, Adrian E Raftery, Kenneth M Dombek, Jun Zhu, Eric E Schadt, Roger E Bumgarner and Ka Yee Yeung
    Citation: BMC Systems Biology 2012 6:101
  19. Statistical approaches to describing the behaviour, including the complex relationships between input parameters and model outputs, of nonlinear dynamic models (referred to as metamodelling) are gaining more a...

    Authors: Kristin Tøndel, Ulf G Indahl, Arne B Gjuvsland, Stig W Omholt and Harald Martens
    Citation: BMC Systems Biology 2012 6:88
  20. Identification of essential proteins plays a significant role in understanding minimal requirements for the cellular survival and development. Many computational methods have been proposed for predicting essen...

    Authors: Wei Peng, Jianxin Wang, Weiping Wang, Qing Liu, Fang-Xiang Wu and Yi Pan
    Citation: BMC Systems Biology 2012 6:87
  21. Complete transcriptional regulatory network inference is a huge challenge because of the complexity of the network and sparsity of available data. One approach to make it more manageable is to focus on the inf...

    Authors: Michalis K Titsias, Antti Honkela, Neil D Lawrence and Magnus Rattray
    Citation: BMC Systems Biology 2012 6:53
  22. The quantification of metabolic fluxes is gaining increasing importance in the analysis of the metabolic behavior of biological systems such as organisms, tissues or cells. Various methodologies (wetlab or dry...

    Authors: Hendrik Rohn, Anja Hartmann, Astrid Junker, Björn H Junker and Falk Schreiber
    Citation: BMC Systems Biology 2012 6:33
  23. Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large num...

    Authors: Min Li, Hanhui Zhang, Jian-xin Wang and Yi Pan
    Citation: BMC Systems Biology 2012 6:15
  24. Mathematical models of dynamical systems facilitate the computation of characteristic properties that are not accessible experimentally. In cell biology, two main properties of interest are (1) the time-period...

    Authors: Thomas Maiwald, Julie Blumberg, Andreas Raue, Stefan Hengl, Marcel Schilling, Sherwin KB Sy, Verena Becker, Ursula Klingmüller and Jens Timmer
    Citation: BMC Systems Biology 2012 6:13
  25. The creation and modification of genome-scale metabolic models is a task that requires specialized software tools. While these are available, subsequently running or visualizing a model often relies on disjoin...

    Authors: Joost Boele, Brett G Olivier and Bas Teusink
    Citation: BMC Systems Biology 2012 6:8
  26. The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum In...

    Authors: Dagmar Waltemath, Richard Adams, Frank T Bergmann, Michael Hucka, Fedor Kolpakov, Andrew K Miller, Ion I Moraru, David Nickerson, Sven Sahle, Jacky L Snoep and Nicolas Le Novère
    Citation: BMC Systems Biology 2011 5:198
  27. Elementary flux modes (EFM) are unique and non-decomposable sets of metabolic reactions able to operate coherently in steady-state. A metabolic network has in general a very high number of EFM reflecting the t...

    Authors: Ana R Ferreira, João ML Dias, Ana P Teixeira, Nuno Carinhas, Rui MC Portela, Inês A Isidro, Moritz von Stosch and Rui Oliveira
    Citation: BMC Systems Biology 2011 5:181
  28. Proteins, individual cells, and cell populations denote different levels of an organizational hierarchy, each of which with its own dynamics. Multi-level modeling is concerned with describing a system at these...

    Authors: Carsten Maus, Stefan Rybacki and Adelinde M Uhrmacher
    Citation: BMC Systems Biology 2011 5:166
  29. Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to...

    Authors: Miranda D Stobbe, Sander M Houten, Gerbert A Jansen, Antoine HC van Kampen and Perry D Moerland
    Citation: BMC Systems Biology 2011 5:165
  30. We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and hav...

    Authors: Katerina Tashkova, Peter Korošec, Jurij Šilc, Ljupčo Todorovski and Sašo Džeroski
    Citation: BMC Systems Biology 2011 5:159
  31. Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict...

    Authors: Paul A Jensen, Kyla A Lutz and Jason A Papin
    Citation: BMC Systems Biology 2011 5:147
  32. Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on ...

    Authors: Robert Hoehndorf, Michel Dumontier, John H Gennari, Sarala Wimalaratne, Bernard de Bono, Daniel L Cook and Georgios V Gkoutos
    Citation: BMC Systems Biology 2011 5:124
  33. While functional genomics, focused on gene functions and gene-gene interactions, has become a very active field of research in molecular biology, equivalent methodologies embracing the environment and gene-env...

    Authors: Ana P Teixeira, João ML Dias, Nuno Carinhas, Marcos Sousa, João J Clemente, António E Cunha, Moritz von Stosch, Paula M Alves, Manuel JT Carrondo and Rui Oliveira
    Citation: BMC Systems Biology 2011 5:92