Dynamic programming has been one of the most efficient approaches to sequence analysis and structure prediction in biology. However, their performance is limited due to the drastic increase in both the number of biolo...
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Dynamic programming has been one of the most efficient approaches to sequence analysis and structure prediction in biology. However, their performance is limited due to the drastic increase in both the number of biological data and variety of the computer architectures. With regard to such predicament, this paper creates excellent algorithms aimed at addressing the challenges of improving memory efficiency and network latency tolerance for nonserial polyadic dynamic programming where the dependences are nonuniform. By relaxing the nonuniform dependences, we proposed a new cache oblivious scheme to enhance its performance on memory hierarchy architectures. Moreover we develop and extend a tiling technique to parallelize this nonserial polyadic dynamic programming using an alternate block-cyclic mapping strategy for balancing the computational and memory load, where an analytical parameterized model is formulated to determine the tile volume size that minimizes the total execution time and an algorithmic transformation is used to schedule the tile to overlap communication with computation to further minimize communication overhead on parallel architectures. The numerical experiments were carried out on several high performance computersystems. The new cache-oblivious dynamic programming algorithm achieve 2-10 speedup and the parallel tiling algorithm with communication-computation overlapping shows a desired potential for fine-grained parallel computing on massively parallel computersystems
Wireless sensor network (WSN), which is integrated with many technologies such as sensor, embedded computing, wireless communication and distributed information processing etc., is becoming an important branch of ubiq...
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Wireless sensor network (WSN), which is integrated with many technologies such as sensor, embedded computing, wireless communication and distributed information processing etc., is becoming an important branch of ubiquitous computing research. WSN is composed of a large number of distributed sensor nodes, so to ensure the sensor nodes dependable is essential to security of whole network. By introducing a lightweight tamper-resistance design based on security co-processor into sensor nodes, this paper loosens up the security assumptions of WSN, and redefines the objectives of WSN security. Based on such secure infrastructure, the paper also proposes a concise and effective key pre-distribution scheme, in which each node needs to send only one cluster key announcement message and cluster key net can be set up within neighborhood
3D models are a new kind of cross-media resource which can be frequently seen in the network. Since the amount of them is very huge now, content-based retrieval can help to recognize a certain object or retrieve simil...
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3D models are a new kind of cross-media resource which can be frequently seen in the network. Since the amount of them is very huge now, content-based retrieval can help to recognize a certain object or retrieve similar ones from the giant database. This paper presents a new method for deriving 3D moment invariants and uses them as shape descriptors for the representation of 3D models. They are insensitive to surface noise and can be used in pervasive environment conveniently. We also illustrate how to build up experimental system and simulate 3D shape retrieval in wireless environment
Aiming at the two main shortcomings in Homology Modeling, we have designed and established a domain clustering database. Searching the database is a fundamental work for it. However, current alignment algorithms are m...
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Aiming at the two main shortcomings in Homology Modeling, we have designed and established a domain clustering database. Searching the database is a fundamental work for it. However, current alignment algorithms are mainly based on the sequences, ignoring the structure conservation in domain. This paper proposed a profile-based alignment which considers the structure information into the profile, based on the character of our domain database. We designed an experiment within the database. The results show that both the quality and sensitivity of our scheme are better than pure Smith-Waterman and sequence-based profile algorithms. We strongly believe that this work can help to improve the protein structure prediction
Recently, large-scale protein-protein interactions were recovered using the similar two-hybrid system for the model systems. This information allows us to investigate the protein interaction network from a systematic ...
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Recently, large-scale protein-protein interactions were recovered using the similar two-hybrid system for the model systems. This information allows us to investigate the protein interaction network from a systematic point of view. However, experimentally determined interactions are susceptible to errors. A previous assessment estimated that only ~10% of the interactions can be supported by more than one independent experiment, and about half of the interactions may be false positives. These false positives might unnecessarily link unrelated proteins, resulting in huge apparent interaction clusters, which complicate elucidation for the biological importance of these interactions. Address this problem, we present an approach to integrate, assess and characterize all available protein-protein interactions in model organisms yeast and fly. We first integrate all available protein-protein interaction databases of yeast and fly, and merge all the datasets. We then use machine learning techniques to score the reliability for each interaction, and to rigorously validate the scoring scheme of yeast protein-protein interactions from different aspects. Our results show that this scoring scheme provides a good basis for selecting reliable protein-protein interaction dataset
This book constitutes the refereed proceedings of six workshops of the 14th International Conference on Web-Age Information Management, WAIM 2013, held in Beidaihe, China, June 2013. The 37 revised full papers are org...
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ISBN:
(数字)9783642395277
ISBN:
(纸本)9783642395260
This book constitutes the refereed proceedings of six workshops of the 14th International Conference on Web-Age Information Management, WAIM 2013, held in Beidaihe, China, June 2013. The 37 revised full papers are organized in topical sections on the six following workshops: The International Workshop on Big Data Management on Emerging Hardware (HardBD 2013), the Second International Workshop on Massive Data Storage and Processing (MDSP 2013), the First International Workshop on Emergency Management in Big Data Age (BigEM 2013), the International Workshop on Trajectory Mining in Social Networks (TMSN 2013), the First International Workshop on Location-based Query Processing in Mobile Environments (LQPM 2013), and the First International Workshop on Big Data Management and Service (BDMS 2013).
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