The Center for the Multiscale Analysis of Genetic Networks (MAGNet, http://magnet.c2b2.columbia.edu) was established in 2005, with the mission of providing the biomedical research community with Structural and Systems Biology algorithms and software tools for the dissection of molecular interactions and for the interaction-based elucidation of cellular phenotypes. Over the last 7 years, MAGNet investigators have developed many novel analysis methodologies, which have led to important biological discoveries, including understanding the role of the DNA shape in protein-DNA binding specificity and the discovery of genes causally related to the presentation of malignant phenotypes, including lymphoma, glioma, and melanoma. Software tools implementing these methodologies have been broadly adopted by the research community and are made freely available through geWorkbench, the Center's integrated analysis platform. Additionally, MAGNet has been instrumental in organizing and developing key conferences and meetings focused on the emerging field of systems biology and regulatory genomics, with special focus on cancer-related research.

SUMMARY: geWorkbench (genomics Workbench) is an open source Java desktop application that provides access to an integrated suite of tools for the analysis and visualization of data from a wide range of genomics domains (gene expression, sequence, protein structure and systems biology). More than 70 distinct plug-in modules are currently available implementing both classical analyses (several variants of clustering, classification, homology detection, etc.) as well as state of the art algorithms for the reverse engineering of regulatory networks and for protein structure prediction, among many others. geWorkbench leverages standards-based middleware technologies to provide seamless access to remote data, annotation and computational servers, thus, enabling researchers with limited local resources to benefit from available public infrastructure. AVAILABILITY: The project site (http://www.geworkbench.org) includes links to self-extracting installers for most operating system (OS) platforms as well as instructions for building the application from scratch using the source code [which is freely available from the project's SVN (subversion) repository]. geWorkbench support is available through the end-user and developer forums of the caBIG Molecular Analysis Tools Knowledge Center, https://cabig-kc.nci.nih.gov/Molecular/forums/

Article Sequence homology detection through large scale pattern discovery Share on Authors: Aris Floratos Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY and Courant Institute of Mathematical Sciences, New York University, New York, NY Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY and Courant Institute of Mathematical Sciences, New York University, New York, NYView Profile , Isidore Rigoutsos Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NYView Profile , Laxmi Parida Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY and Courant Institute of Mathematical Sciences, New York University, New York, NY Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY and Courant Institute of Mathematical Sciences, New York University, New York, NYView Profile , Gustova Stolovitzky Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NYView Profile , Yuan Gao Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY Computational Biology Center, IBM Research Division, T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NYView Profile Authors Info & Claims RECOMB '99: Proceedings of the third annual international conference on Computational molecular biologyApril 1999 Pages 164–173https://doi.org/10.1145/299432.299477Online:01 April 1999Publication History 6citation379DownloadsMetricsTotal Citations6Total Downloads379Last 12 Months2Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

MOTIVATION: The discovery of motifs in biological sequences is an important problem. RESULTS: This paper presents a new algorithm for the discovery of rigid patterns (motifs) in biological sequences. Our method is combinatorial in nature and able to produce all patterns that appear in at least a (user-defined) minimum number of sequences, yet it manages to be very efficient by avoiding the enumeration of the entire pattern space. Furthermore, the reported patterns are maximal: any reported pattern cannot be made more specific and still keep on appearing at the exact same positions within the input sequences. The effectiveness of the proposed approach is showcased on a number of test cases which aim to: (i) validate the approach through the discovery of previously reported patterns; (ii) demonstrate the capability to identify automatically highly selective patterns particular to the sequences under consideration. Finally, experimental analysis indicates that the algorithm is output sensitive, i.e. its running time is quasi-linear to the size of the generated output.