Subsequently, we can integrate the new compiler into Mango Graph Studio and release version 2.0 to the public, and then users can take advantage of all new features we have created during this project and apply them toward solving their bioinformatic and other graph analytic problems. Therefore, there is no doubt that the Gel 2.0 compiler can be completed later, likely during Year 1 of the Phase II work. Although the Gel 2.0 compiler has not been completed due to the additional language design decisions and compiler implementation needs uncovered during the Phase I project, we have resolved all design decisions and made solid progresses toward its completion.
Designing in brl cad code#
We have also studied the optimal approach to integrate our existing many-core GPU accelerated graph traversal code with Mango Graph Studio so certain time-consuming graph computations on graphs in billion-node scales can be seamlessly pushed onto GPUs and got sped up there. Specifically, during this Phase I Project a new version of the Graph Exploration Language (Gel) has been designed to make it a general-purpose programming language, the implementation of the new Gel version 2 compiler has gone underway, and some practical Mango applications have also been developed to solve PCR primer design problems and short-interfering RNA (siRNA) design problems.
Mango Graph Studio has been published in academic journals, and it is the focus of this SBIR Phase I project to advance its applications in bioinformatic research including systems biology, and to promote its uses by scientists in more research fields. Mango Graph Studio strikes an optimal balance among its ease of uses (has a modern graphical user interface), flexibility in applications (comes with the Graph Exploration Language), computational power (automatically takes advantage of multi-core CPUs and many-core GPUs) and data scalability (handles million-node graphs easily even on personal computers). It comes at the right time when biological BIG DATA are no longer just the problems of large genome research centers but have gradually become the problems of every biologist. This preferred platform is Mango Graph Studio™.
Designing in brl cad software#
Independent biologists working on their respective biological research endeavors may prefer a novel software platform that can enable them to perform sophisticated systems biology analyses without the need to learn professional computer science skills. Although software engineers and biologists can form interdisciplinary research teams to solve systems biology problems together, it is not always efficient or possible to form such a team. Software engineers who are capable of these in-depth programming efforts may not be able to form biological analysis algorithms or to interpret more » the analysis results, while biologists who can formulate the hypotheses for analyses and understand the analysis results may not be good at programming. However, construction and manipulation of complex graph or network data structures to represent the heterogeneous data that are linked to each other require computer science skills. Systems biology aims at utilizing these data to help model complex biological systems and further our understanding of living beings, so we may cure more diseases or harvest more renewable bio-energies in the future. Modern genomic and post-genomic research produced huge amounts of heterogeneous data that must be integrated and analyzed together.
0 kommentar(er)
