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A Finney

Publications and source records attributed to A Finney.

7 recordsLinked to original sources
PubMed2004

Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project.

Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

Biochemistry↗
PubMed2003

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

MOTIVATION: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY: The specification of SBML Level 1 is freely available from http://www.sbml.org/

Database Management Systems↗
PubMed2003

Systems biology markup language: Level 2 and beyond.

The SBML (systems biology markup language) is a standard exchange format for computational models of biochemical networks. We continue developing SBML collaboratively with the modelling community to meet their evolving needs. The recently introduced SBML Level 2 includes several enhancements to the original Level 1, and features under development for SBML Level 3 include model composition, multistate chemical species and diagrams.

Computational Biology↗
PubMed2002

The ERATO Systems Biology Workbench: enabling interaction and exchange between software tools for computational biology.

Researchers in computational biology today make use of a large number of different software packages for modeling, analysis, and data manipulation and visualization. In this paper, we describe the ERATO Systems Biology Workbench (SBW), a software framework that allows these heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' data and algorithmic capabilities. Our goal is to create a simple, open-source software infrastructure which is effective, easy to implement and easy to understand. SBW uses a broker-based architecture and enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe the SBW architecture and the current set of modules, as well as alternative implementation technologies.

Computational Biology↗
PubMed1993

Measurement and prediction of the short-term response of soft tissue sarcomas to chemotherapy.

BACKGROUND: Preoperative chemotherapy has been advocated for the treatment of soft tissue sarcomas, yet there is little information about how these tumors respond pathologically to therapy or whether tumor response can be predicted from a pretreatment biopsy. METHODS: Biopsy was done of 25 intermediate- or high-grade soft tissue sarcomas before they were treated with three cycles of doxorubicin and cisplatin and resected. The authors compared the pathologic features of the treated tumors with clinical and radiologic evidence of response to identify the pathologic features that best reflected chemotherapeutic effect. They analyzed the pretreatment biopsy specimens by light microscopic study and flow cytometry to identify parameters that predict short-term response to chemotherapy. RESULTS: In the treated tumors, the clearest indicator of early chemotherapeutic effect was the percentage of the resected mass composed of viable neoplasm. Eleven of 25 resection specimens contained less than 15% viable neoplasm (patients with pathologic response); 9 of these had 5% or less. Flow cytometric estimates of the proliferative rate in the initial biopsy specimen predicted early chemotherapeutic effect; 7 of 10 tumors with S-phase fractions (SPF) greater than 6% responded pathologically, whereas only 3 of 12 tumors with lower SPF responded (P = 0.041). Initial tumor grade, cell type, percent tumor necrosis, mitotic rate, cellularity, and ploidy did not predict chemotherapy response. CONCLUSION: These results indicate that soft tissue sarcomas often respond dramatically to chemotherapy, that the amount of residual viable sarcoma is an indicator of short-term effect, and that flow cytometric estimates of cell proliferation predict early response to chemotherapy.

Adolescent↗