The business machine in biology: the commercialization of AI in the life science

This paper traces one important trajectory in the history of expert systems. Through a collaboration between Edward Feigenbaum and the geneticist Joshua Lederberg, Nobel Laureate in Medicine, AI became deeply connected to the life sciences. Biology was a crucial test-bed for some of Feigenbaums systems and, in the long term, these systems had a transformative effect on biology. In particular, the work of Feigenbaum and his collaborators and students, brought biology and computing together in especially powerful ways. We now take for granted that biology can be computerized we have whole sub-disciplines such as bioinformatics, biocomputing, and computational biology devoted to the task of studying life as information. The computer systems and software that Feigenbaums lab helped to develop played an important role in establishing the possibility of these kinds of work

Selected papers from the 15th Annual Bio-Ontologies special interest group meeting

© 2013 Soldatova et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Over the 15 years, the Bio-Ontologies SIG at ISMB has provided a forum for discussion of the latest and most innovative research in the bio-ontologies development, its applications to biomedicine and more generally the organisation, presentation and dissemination of knowledge in biomedicine and the life sciences. The seven papers and the commentary selected for this supplement span a wide range of topics including: web-based querying over multiple ontologies, integration of data, annotating patent records, NCBO Web services, ontology developments for probabilistic reasoning and for physiological processes, and analysis of the progress of annotation and structural GO changes

A Computational Approach for Identifying Plant-Based Foods for Addressing Vitamin Deficiency Diseases

Vitamins are nutrients that are essential to human health, and deficiencies have been shown to cause severe diseases. In this study, a computational approach was used to identify vitamin deficiency diseases and plant-based foods with vitamin content. Data from the United States Department of Agriculture Standard Reference (SR27), National Library of Medicine\u27s Medical Subject Headings and MEDLINE, and Wikipedia were combined to identify vitamin deficiency diseases and vitamin content of plant-based foods. A total of 41,584 vitamin-disease associations were identified from MEDLINE-indexed articles as well as from entries in Wikipedia. The SR27 identified 1912 foods that contained at least one vitamin, with an average of 1276 foods per vitamin. Vitamin B12 and D contained the fewest number of foods (n=135 and 70, respectively). The results of this study establish the foundation for developing a process to link vitamin deficiency diseases to vitamin-rich foods

Dynamic Modeling and Statistical Analysis of Event Times

This review article provides an overview of recent work in the modeling and analysis of recurrent events arising in engineering, reliability, public health, biomedicine and other areas. Recurrent event modeling possesses unique facets making it different and more difficult to handle than single event settings. For instance, the impact of an increasing number of event occurrences needs to be taken into account, the effects of covariates should be considered, potential association among the interevent times within a unit cannot be ignored, and the effects of performed interventions after each event occurrence need to be factored in. A recent general class of models for recurrent events which simultaneously accommodates these aspects is described. Statistical inference methods for this class of models are presented and illustrated through applications to real data sets. Some existing open research problems are described.Comment: Published at http://dx.doi.org/10.1214/088342306000000349 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Diversity in Academic Biomedicine: An Evaluation of Education and Career Outcomes with Implications for Policy

Currently, the U.S. population is undergoing major racial and ethnic demographic shifts that could affect the pool of individuals interested in pursuing a career in biomedical research. To achieve its mission of improving health, the National Institutes of Health must recruit and train outstanding individuals for the biomedical workforce. In this study, we examined the educational transition rates in the biomedical sciences by gender, race, and ethnicity, from high school to academic career outcomes. Using a number of educational databases, we investigated gender and racial/ethnic representation at typical educational and career milestones en route to faculty careers in biomedicine. We then employed multivariate regression methods to examine faculty career outcomes, using the National Science Foundation’s Survey of Doctorate Recipients. We find that while transitions between milestones are distinctive by gender and race/ethnicity, the transitions between high school and college and between college and graduate school are critical points at which underrepresented minorities are lost from the biomedical pipeline, suggesting some specific targets for policy intervention

Quantitative surface normal measurement by a wavefront camera

A compact wavefront camera that allows users to quantitatively measure the intensity and wavefront at a remote object plane is reported. The camera is built from a chip-scale wavefront sensor that we previously developed. By measuring the wavefront of the image and calibrating the wavefront relationship between the image and object planes, the wavefront at the object plane can be computed and the surface normal of the object can be derived. We built a prototype camera and calibrated the wavefront relationship. In a proof-of-concept experiment, a set of concave mirrors with different focal lengths (50–200 mm), were imaged. The results agree well with their expected values. To demonstrate the application of the camera, we applied this method to measure the deformation of a microfluidic channel under pressure

Automation Process for Morphometric Analysis of Volumetric CT Data from Pulmonary Vasculature in Rats

With advances in medical imaging scanners, it has become commonplace to generate large multidimensional datasets. These datasets require tools for a rapid, thorough analysis. To address this need, we have developed an automated algorithm for morphometric analysis incorporating A Visualization Workshop computational and image processing libraries for three-dimensional segmentation, vascular tree generation and structural hierarchical ordering with a two-stage numeric optimization procedure for estimating vessel diameters. We combine this new technique with our mathematical models of pulmonary vascular morphology to quantify structural and functional attributes of lung arterial trees. Our physiological studies require repeated measurements of vascular structure to determine differences in vessel biomechanical properties between animal models of pulmonary disease. Automation provides many advantages including significantly improved speed and minimized operator interaction and biasing. The results are validated by comparison with previously published rat pulmonary arterial micro-CT data analysis techniques, in which vessels were manually mapped and measured using intense operator intervention