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Massachusetts Institute of Technology

Language & tools for context-aware biology

Abstract

dc:description.abstract

Current biological research workflows make use of disparate, poorly integrated systems that cause large mental burden on the scientist leading to mistakes on often long, complex and costly experimental procedures. The lack of open tools to assist in the collection of distributed experimental conditions and data is largely responsible making protocols difficult to debug and laboratory practice hard to learn. In this thesis, we describe an open Protocol Descriptor Language (PDL) and system to enable a context-rich, quantitative approach to biological research. We detail the development of a closed-loop pipetting technology and a wireless, sample temperature sensor that integrate with our Protocol Description platform enabling novel, real-time experimental feedback to the researcher thereby reducing mistakes and increasing overall scientific reproducibility.

Degree

thesis:*
Department dc:contributor.department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2014

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Fracchia, Charles (Charles Victor)
Advisor dc:contributor.advisor
  • Joseph Jacobson.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/100890
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/100890

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Fracchia, Charles (Charles Victor). Language & tools for context-aware biology. Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/100890