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Computational Health Informatics Program (BCH)

Location: Boston Children's Hospital, Computational Health Informatics Program, One Autumn 535, Mail Stop BCH3187, 300 Longwood Avenue, Boston, MA 02115

Summary:

The Boston Children's Hospital Computational Health Informatics Program (CHIP) is a multidisciplinary applied research and education program. Informatics has become a major theme and methodology for biomedical science, health care delivery, and public health. Biomedical informatics involves modeling and understanding the cognitive, information processing and communication tasks of biomedical science, medical practice, education and research. The field is inherently interdisciplinary, drawing on traditional biomedical disciplines, the science and technology of computing, data science, biostatistics, epidemiology, decision sciences, population health, omics, implementation science, and health care policy and management. Our faculty are trained in medicine, data scientice, computer science, mathematics and epidemiology.

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Services

  • Training and consultation in academic research and industrial informatics ( Training service )

    "A wide variety of course offerings at Harvard, MIT, Tufts, and Boston University, seminars, journal clubs, and other forums for exchange of information provide all trainees with opportunities to learn about the variety of research being conducted at the various laboratories and in the affiliated institutions, as well as in the larger field of biomedical informatics."

    CHIP also provides research and informatics consultation.

Software

  • Growth Calculator Software ( Software )

  • HealthMap Software ( Software )

    HealthMap brings together disparate data sources to achieve a unified and comprehensive view of the current global state of infectious diseases and their effect on human and animal health. This freely available Web site integrates outbreak data of varying reliability, ranging from news sources (such as Google News) to curated personal accounts (such as ProMED) to validated official alerts (such as World Health Organization). Through an automated text processing system, the data is aggregated by disease and displayed by location for user-friendly access to the original alert. HealthMap provides a jumping-off point for real-time information on emerging infectious diseases and has particular interest for public health officials and international travelers.

  • Indivo Software ( Software )

    A distributed, web-based, personally controlled electronic medical record system, built to public standards, and written in open source code.

  • MAPPER ( Software )

    "MAPPER is a platform for the computational identification of transcription factor binding sites (TFBSs) in multiple genomes. It uses an innovative technique that combines TRANSFAC® and JASPAR data with the search power of profile hidden Markov models. Based on curated nucleotide sequences of experimentally determined binding sites retrieved from the two databases we built profile hidden Markov models for a large number of transcription factors. We then used this models to develop a search engine for the retrieval of putative TFBSs in a known gene or an uploaded sequence, and to generate a large database of such sites identified in the upstream sequences of all the human, mouse and Drosophila genes."

  • SNPper Software ( Software )

    A tool to search for and analyze Single-Nucleotide Polymorphisms (SNPs); retrieve known SNPs by position or by association with a gene; save, filter, analyze, display or export SNP sets; and explore known genes using names or chromosome positions.

  • START ( Software )

    "START is a tool for the automatic processing of Serial Analysis of Chromatin Occupancy (SACO) data. The program uses as input the sequences of inserts, in FastA format, from a SACO library from which it extracts the SACO tags, maps them to genomic locations and annotates them returning detailed information regarding the genes and genomic elements found in their vicinity. START also makes use of the MAPPER database to predict putative transcription factor binding sites in the vicinity of the tags that fall within the upstream regulatory regions of the genes."


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Last updated: 2015-08-24T15:33:43.575-05:00

Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016