Robert L. Martino

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A massive volume of biological sequence data is available in over 36 different databases worldwide, including the sequence data generated by the Human Genome project. These databases, which also contain biological and bibliographical information, are growing at an exponential rate. Consequently, the computational demands needed to explore and analyze the(More)
Three dimensional image reconstruction from cryo-electron micrographs allows the capsid structures of icosahedral viruses to be studied. The most computationally demanding stages of the reconstruction process are those that find and refine the orientations of the virus particles. We have devised and implemented parallel solutions to the problem of(More)
Scalable parallel computer architectures provide the computational performance needed for advanced biomedical computing problems. The National Institutes of Health have developed a number of parallel algorithms and techniques useful in determining biological structure and function. These applications include processing electron micrographs to determine the(More)
Many different methods have been presented for aligning multiple biological sequences. These methods can be classified into three categories: rigorous, tree-based, and iterative. The rigorous method, which always generates the optimal alignment, requires memory space and computation time proportional to the product of the sequence lengths. Even for a modest(More)
Clinical research approval processes are complex since they involve human subject welfare as well as regulatory and ethical concerns. Typically, clinical research institutions have an elaborate established review process; the labor-intensive and time-consuming nature of this process can result in approval delays thus significantly impacting the biomedical(More)
We present a parallel computational method for retrieving similar sequences from large genetic and protein databases using a dynamic programming comparison algorithm. Two previously published parallel methods for performing this task are first discussed and evaluated. The advantages of these two parallel methods are combined and incorporated into our new(More)
This paper describes potential strategies for data modeling and implementation as part of the general architecture of CSIS, a clinical study and informatics system that has been developed for the National Institute of Neuroscience and Stroke (NINDS). We discuss the NINDS requirements and how they influenced the system design, with an emphasis on dynamic(More)
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