Absolute or relative transcript amounts measured through high-throughput technologies (e.g., microarrays) are now commonly used in bioinformatics analysis, such as gene clustering and DNA binding motif finding. However, transcription rates that represent mRNA synthesis may be more relevant in these analyses.Because transcription rates are not equivalent to transcript amounts unless the mRNA degradation rates as well as other factors that affect transcript amount are identical across different genes, the use of transcription rates in bioinformatics analysis may lead to a better description of the relationships among genes and better identification of genomic signals. In this article, we propose to use experimentally measured mRNA decay rates and mRNA transcript amounts to jointly infer transcription rates, and then use the inferred transcription rates in downstream analyses. For gene expression similarity analysis, we find that there tends to be higher correlations among co-regulated genes when transcription-rate-based correlations are used compared to those based on transcript amounts. In the context of identifying DNA binding motifs, using inferred transcription rates leads to more significant findings than those based on transcript amounts. These analyses suggest that the incorporation of mRNA decay rates and the use of the inferred transcription rates can facilitate the study of gene regulations and the reconstruction of transcriptional regulatory networks.

Determining how cells regulate their transcriptional response to extracellular signals is key to the understanding of complex eukaryotic systems. This study was initiated with the goals of furthering the study of mammalian transcriptional regulation and analyzing the relative benefits of related computational methodologies. One dataset available for such an analysis involved gene expression profiling of the early growth factor response to platelet derived growth factor (PDGF) in a human glioblastoma cell line; this study differentiated genes whose expression was regulated by signaling through the phosphoinositide-3-kinase (PI3K) versus the extracellular-signal regulated kinase (ERK) pathways. We have compared the inferred transcription factors from this previous study with additional predictions of regulatory transcription factors using two alternative promoter sequence analysis techniques. This comparative analysis, in which the algorithms predict overlapping, although not identical, sets of factors, argues for meticulous benchmarking of promoter sequence analysis methods to determine the positive and negative attributes that contribute to their varying results. Finally, we inferred transcriptional regulatory networks deriving from various signaling pathways using the CARRIE program suite. These networks not only included previously described transcriptional features of the response to growth signals, but also predicted new regulatory features for the propagation and modulation of the growth signal.

With several rice genome projects approaching completion gene prediction/finding by computer algorithms has become an urgent task. Two test sets were constructed by mapping the newly published 28,469 full-length KOME rice cDNA to the RGP BAC clone sequences of Oryza sativa ssp. Japonica : a single-gene set of 550 sequences and a multi-gene set of 62 sequences with 271 genes. These data sets were used to evaluate five ab initio gene prediction programs: RiceHMM, GlimmerR, GeneMark, FGENSH and BGF. The predictions were compared on nucleotide, exon and whole gene structure levels using commonly accepted measures and several new measures. The test results show a progress in performance in chronological order. At the same time complementarity of the programs hints on the possibility of further improvement and on the feasibility of reaching better performance by combining several gene-finders.

An increasing number of structural homology search tools, mostly based on profile stochastic context-free grammars (SCFGs) have been recently developed for the non-coding RNA gene identification. SCFGs can include statistical biases that often occur in RNA sequences, necessary to profile specific RNA structures for structural homology search. In this paper, a succinct stochastic grammar model is introduced for RNA that has competitive search effectiveness. More importantly, the profiling model can be easily extended to include pseudoknots, structures that are beyond the capability of profile SCFGs. In addition, the model allows heuristics to be exploited, resulting in a significant speed-up for the CYK algorithm-based search.

A new method for intrinsic terminator prediction based on Rnall, an RNA local secondary structure prediction algorithm developed recently, and two U-tail score schemas are developed. By optimizing three parameters (thermodynamic energy of RNA hairpin structure, U-tail T weight, and U-tail hybridization energy), the method can recognize 92.25 of known terminators while rejecting 98.48 of predicted RNA local secondary structures in coding regions (negative control) as false intrinsic terminators in E. coli. This method was applied to scan the genome of Synechococcus sp. WH8102, and we predicted 266 intrinsic terminators, which included 232 protein-coding genes, 12 tRNA genes, and 3 rRNA genes. About 17\% of these terminators are located at the end of operons. It is also identified 8 pairs of bio-directional terminators. The method for intrinsic terminator prediction has been incorporated into Rnall, which is available at http://digbio.missouri.edu/$\sim$wanx/Rnall/.

De novo sequencing is one of the most promising proteomics techniques for identification of protein post-translation modifications (PTMs) in studying protein regulations and functions. We have developed a computer tool PRIME for identification of b and y ions in tandem mass spectra, a key challenging problem in de novo sequencing. PRIME utilizes a feature that ions of the same and different types follow different mass-difference distributions to separate b from y ions correctly. We have formulated the problem as a graph partition problem.A linear integer-programming algorithm has been implemented to solve the graph partition problem rigorously and efficiently. The performance of PRIME has been demonstrated on a large amount of simulated tandem mass spectra derived from Yeast genome and its power of detecting PTMs has been tested on 216 simulated phosphopeptides.

Here, the issue of robustness analysis of cell JAK-STAT signal transduction networks is addressed. This is investigated upon a mathematical model of IFN-γ induced JAK-STAT signaling pathway by applying robustness analysis which is based on a broad range of simultaneous and systematical parameters variation. The effects of the variations of the initial signal proteins' concentrations on the output of this system are also studied. The study demonstrates that the JAK-STAT signaling pathway is robust with respect to its ``signal time'' and ``signal duration'', but sensitive with respect to its ``signal amplitude''. These analysis results can point to experimental designs that can further test how the pathway activity can be perturbed.

The paper presents three formal proving methods for generalized weakly ground terminating property, I.e., weakly terminating property in a restricted domain of a term rewriting system, one with structural induction, one with cover-set induction, and the third without induction, and describes their mechanization based on a meta-computation model for term rewriting systems---dynamic term rewriting calculus. The methods can be applied to non-terminating, non-confluent and or non-left-linear term rewriting systems. They can do "forward proving" by applying propositions in the proof, as well as "backward proving" by discovering lemmas during the proof.

Action refinement for real-time concurrent processes with urgent interactions is studied, where a partial-order setting, I.e., timed bundle event structures, is used as the system model and a real-time LOTOS-like process algebra is used as the specification language. It is shown that the proposed refinement approaches have the commonly expected properties: (1) the behaviour of the refined process can be inferred compositionally from the behaviour of the original process and from the behaviour of the processes substituted for actions; (2) the timed extensions of pomset (partially ordered multiset) trace equivalence and history preserving bisimulation equivalence are both congruences under the refinement; (3) the syntactic and semantic refinements coincide up to the aforementioned equivalence relations with respect to a cpo-based denotational semantics.

A new approach to domain-specific reasoning is presented that is based on a type-theoretic logical framework (LF) but does not require the user to be an expert in type theory. The concepts of the domain and its related reasoning systems are formalized in LF, but the user works with the system through a syntax and interface appropriate to his/her work. A middle layer provides translation between the user syntax and LF, and allows additional support for reasoning (e.g., model checking). Thus, the complexity of the logical framework is hidden but the benefits of using type theory and its related tools are retained, such as precision and machine-checkable proofs. This approach is investigated through a number of case studies: here, the authors consider the verification of properties of concurrency. The authors have formalized a specification language (CCS) and logic (μ-calculus) in LF, together with useful lemmas, and a user-oriented syntax has been designed. The authors demonstrate the approach with simple examples. However, applying lemmas to objects introduced by the user may result in framework-level objects which cannot be translated back to the user level.The authors discuss this problem, define a notion of adequacy, and prove that in this case study, translation can always be reversed.

One of the important topics in the study of contraction inference relations is to establish the representation theorems for them. Various methods have been employed for giving representation of a broad class of contraction operations. However, there was not any canonical approach to dealing with the representation results for the contraction relations in the literature. Recently, in order to obtain the representation result for recovering contraction inference relations satisfying the condition weak conjunctive inclusion (wci), a notion of an image structure associated with the canonical epistemic state has been introduced. Based on the image structure, this paper establishes three representation results for recovering contraction inference relations which satisfy the conditions CL, CR1 and DR$^{*}$ respectively by the standard epistemic AGM states.A unique technique and uniform proofs to represent these contraction relations are adopted, which could overcome the core objection in previous description of contraction relations. The paper shows as well that the image structure and canonical epistemic states can be used not only to get the representation result for wci-recovering contraction relation, but also to provide semantic characterizations for a wide range of recovering contraction relations.

In the past decade, the booming of Internet challenges the middleware in three aspects: quality of service, balance of changes and stabilization, and across-Internet integration. This paper presents our work on distributed object computing middleware technology for these challenges, as well as the research and development on StarBus+, which is a CORBA standard-compliant middleware suite with the features such as object request broker supporting multi-* quality of service, component model, and integration with Web Service. This paper comprehensively presents the design and characteristics of StarBus+, and demonstrates how StarBus+ is enhanced to address the challenges of Internet computing through three case studies: inter-enterprise integration over Internet, application evolution through dynamic reconfiguration, and great massive information system building. The paper also suggests some research directions which are important for Internet computing.

Document similarity search is to find documents similar to a given query document and return a ranked list of similar documents to users, which is widely used in many text and web systems, such as digital library, search engine, etc. Traditional retrieval models, including the Okapi's BM25 model and the Smart's vector space model with length normalization, could handle this problem to some extent by taking the query document as a long query. In practice, the Cosine measure is considered as the best model for document similarity search because of its good ability to measure similarity between two documents. In this paper, the quantitative performances of the above models are compared using experiments. Because the Cosine measure is not able to reflect the structural similarity between documents, a new retrieval model based on TextTiling is proposed in the paper. The proposed model takes into account the subtopic structures of documents. It first splits the documents into text segments with TextTiling and calculates the similarities for different pairs of text segments in the documents. Lastly the overall similarity between the documents is returned by combining the similarities of different pairs of text segments with optimal matching method. Experiments are performed and results show: 1) the popular retrieval models (the Okapi's BM25 model and the Smart's vector space model with length normalization) do not perform well for document similarity search; 2) the proposed model based on TextTiling is effective and outperforms other models, including the Cosine measure; 3) the methods for the three components in the proposed model are validated to be appropriately employed.

This paper analyzes the sensitivity to noise in BAM (Bidirectional Associative Memory), and then proves the noise immunity of BAM relates not only to the minimum absolute value of net inputs (MAV) but also to the variance of weights associated with synapse connections. In fact, it is a positive monotonically increasing function of the quotient of MAV divided by the variance of weights. Besides, the performance of pseudo-relaxation method depends on learning parameters (lambda and xi), but the relation of them is not linear. So it is hard to find a best combination of lambda and xi which leads to the best BAM performance. And it is obvious that pseudo-relaxation is a kind of local optimization method, so it cannot guarantee to get the global optimal solution. In this paper, a novel learning algorithm EPRBAM (evolutionary psendo-relaxation learning algorithm for bidirectional association memory) employing genetic algorithm and pseudo-relaxation method is proposed to get feasible solution of BAM weight matrix. This algorithm uses the quotient as the fitness of each individual and employs pseudo-relaxation method to adjust individual solution when it does not satisfy constraining condition any more after genetic operation. Experimental results show this algorithm improves noise immunity of BAM greatly. At the same time, EPRBAM does not depend on learning parameters and can get global optimal solution.

An important problem of machine vision is the balance among the efficiency, accuracy and computation cost. The visual system of man can keep watchfulness to the perimeter of a visual field and subtly process information emerging in the center of the visual field at the same time. This kind of requirement assignment of computation can virtually ease the demand of hardware both in quantity and complexity. Therefore designing an artificial model based on biological mechanism is an effective approach. In this paper a multi-layer neural model is designed based on the multi-scale receptive fields of ganglions in retina. The model can keep watch on the periphery part of a scene while processing the center information of the scene. And why it can balance the hardware complexity, processing precision and computational intensity is analyzed. An experiment is done to test the model's sensitivity in watchfulness keeping and its efficiency and veracity in environment sampling. This model may provide valuable inspiration in the implementation of real-time processing and the avoidance of expensive computation cost in machine vision.