Abstract Biology makes things far smaller and more complex than anything produced by human engineering. The biotechnology revolution has for the first time given us the tools necessary to consider engineering on the molecular level. Research in DNA computation, launched by Len Adleman, has opened the door for experimental study of programmable biochemical reactions. Here we focus on a single ...

Quantitative models of biochemical networks (signal transduction cascades, metabolic pathways, gene regulatory circuits) are a central component of modern systems biology. Building and managing these complex models is a major challenge that can benefit from the application of formal methods adopted from theoretical computing science. Here we provide a general introduction to the field of formal...

Praveen Dahiya, Subhash Chand and Neeraj Dilbaghi* Department of Bioand Nanotechnology, Guru Jambheshwar University of Science and Technology, Hisar-125001, Haryana, India Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Hauz Khas, New Delhi-110016, India Present address: Amity Institute of Biotechnology, Amity University, Sector 125, Gautam Buddha Nagar,...

∗To whom correspondence should be addressed †Department of Chemistry, M.V. Lomonosov Moscow State University, 119991 Moscow, Russia ‡Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K. ¶Department of Biochemical Engineering, UCL, Bernard Katz Building, Gordon Street, London, WC1E 0AH, UK. §Department of Physics and Astronomy, Aarhus University, DK-8000 Aa...

Sue-Hong Wang,*,† Tien-Shuh Yang,† Shiang-Ming Lin,† Ming-Shiun Tsai,‡ Shinn-Chih Wu,† and Simon J.T. Mao§,1 *Jen-Te Junior College of Medicine Nursing and Management, Miaoli, Taiwan; †Department of Applied Biology, Pig Research Institute Taiwan, Chunan, Taiwan; ‡Insititute of Molecular Biology, Academic Sinica, Taipei, Taiwan; and §Department of Biological Science and Technology, Research Inst...

This paper provides a brief introduction to learning Bayesian networks from gene-expression data. The method is contrasted with other approaches to the reverse engineering of biochemical networks, and the Bayesian learning paradigm is briefly described. The article demonstrates an application to a simple synthetic toy problem and evaluates the inference performance in terms of ROC (receiver ope...

State Key Lab of Physical Chemistry of S Collaborative Innovation Center of Chem Chemistry and Chemical Engineering, Xia China. E-mail: [email protected] Department of Chemical & Biochemical Chemical Engineering, Xiamen University, [email protected] Department of Chemical and Biomolecula College Park, MD 20740, USA School of Energy Research, Xiamen Univers † Electronic supplementary information ...

Kevin A. Wepasnick , Billy A. Smith , Kaitlin E. Schrote , Hannah K. Wilson , Stephen R. Diegelmann , D. Howard Fairbrother a,d,e,* a Department of Chemistry, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, United States b Department of Chemistry, College of Notre Dame of Maryland, 4701 North Charles Street, Baltimore, MD 21210, United States c Department of Chemical a...

We present an outline of the genome information acquisition (GENIA) project for automatically extracting biochemical information from journal papers and abstracts. GENIA will be available over the Internet and is designed to aid in information extraction, retrieval and visualisation and to help reduce information overload on researchers. The vast repository of papers available online in databas...

PETRICA IANCU1, NICOLETA-GABRIELA STEFAN1, VALENTIN PLESU1*, AURELIAN TOMA1, EMIL STEPAN2 1 Centre for Technology Transfer for the Process Industries, Department of Chemical and Biochemical Engineering, University Politehnica of Bucharest, 1, Gh. Polizu Str., 011061 Bucharest, Roamnia 2 The National Institute for Research & Development in Chemistry and Petrochemistry ICECHIM, 202 Spl. Independe...