82 resultados para regulatory RNA networks


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Purified rinderpest virus was earlier shown to transcribe in vitro, all virus-specific mRNAs with the promoter-proximal N mRNA being the most abundant. Presently, this transcription system has been shown to synthesize full length monocistronic mRNAs comparable to those made in infected cells. Small quantities of bi- and tricistronic mRNAs are also synthesized. Rinderpest virus synthesizes in vitro, a leader RNA of not, vert, similar 55 nucleotides in length. Purified rinderpest virus also exhibits RNA editing activity during the synthesis of P mRNA as shown by primer extension analysis of the mRNA products.

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We study the performance of greedy scheduling in multihop wireless networks where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. Optimal scheduling requires selecting independent sets of maximum aggregate price, but this problem is known to be NP-hard. We propose and evaluate a simple greedy heuristic. Analytical bounds on performance are provided and simulations indicate that the greedy heuristic performs well in practice.

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Design considerations are presented for a dense weather radar network to support multiple services including aviation. Conflicts, tradeoffs and optimization issues in the context of operation in a tropical region are brought out. The upcoming Indian radar network is used as a case study. Algorithms for data mosaicing are briefly outlined.

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In vitro transcription analysis is important to understand the mechanism of transcription. Various assays for the analysis of initiation, elongation and termination form the basis for better understanding of the process. Purified RNA polymerase (RNAP) with high specific activity is necessary to carry out variety of these specific reactions. The RNAP purified from Mycobacterium smegmatis from exponential phase showed low promoter specificity in promoter-polymerase interaction studies. This is due to the presence of a large number of sigma factors during exponential phase and under-representation of sigma(A) required for house-keeping transcription. We describe an in vivo reconstitution of RNAP holoenzyme with sigma(A) and its purification, which resulted in holoenzyme with stoichiometric sigma(A) content. The reconstituted holoenzyme showed enhanced promoter-specific binding and promoter-specific-transcription activity compared to the enzyme isolated using standard procedure. Such in vivo reconstitution of stoichiometric holoenzyme could facilitate promoter-specific transcription assays, especially in organisms which encode a large number of sigma factors.

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Two new coordination polymers [Cu(L-1)(2)](n)(ClO4)(n)center dot 2nH(2)O (1), [Cu(L-2)(2)](n)(ClO4)(n)center dot 2nH(2)O (2) of polydentate imine/pyridyl ligands, L-1 and L-2 with Cu(I) ion have been synthesized and characterized by single crystal X-ray diffraction studies, elemental analyses, IR' UV-vis and NMR spectroscopy. They represent 3-dimensional, sixfold interpenetrating diamondoid network structures having large pores of dimension, 35 x 21 angstrom(2) in 1 and 38 x 19 angstrom(2) in 2, respectively.

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The interdependence of the concept of allostery and enzymatic catalysis, and they being guided by conformational mobility is gaining increased prominence. However, to gain a molecular level understanding of llostery and hence of enzymatic catalysis, it is of utter importance that the networks of amino acids participating in allostery be deciphered. Our lab has been exploring the methods of network analysis combined with molecular dynamics simulations to understand allostery at molecular level. Earlier we had outlined methods to obtain communication paths and then to map the rigid/flexible regions of proteins through network parameters like the shortest correlated paths, cliques, and communities. In this article, we advance the methodology to estimate the conformational populations in terms of cliques/communities formed by interactions including the side-chains and then to compute the ligand-induced population shift. Finally, we obtain the free-energy landscape of the protein in equilibrium, characterizing the free-energy minima accessed by the protein complexes. We have chosen human tryptophanyl-tRNA synthetase (hTrpRS), a protein esponsible for charging tryptophan to its cognate tRNA during protein biosynthesis for this investigation. This is a multidomain protein exhibiting excellent allosteric communication. Our approach has provided valuable structural as well as functional insights into the protein. The methodology adopted here is highly generalized to illuminate the linkage between protein structure networks and conformational mobility involved in the allosteric mechanism in any protein with known structure.

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The nucleotide sequence of a 714 bp BamHI-EcoRI fragment of cucumber chloroplast DNA was determined. The fragment contained a gene for tRNA(Leu) together with its flanking regions. The trnL(CAA) gene sequence is about 99% in similarity to broad bean, cauliflower, maize, spinach and tobacco corresponding genes. The relative expression level of the gene was determined by Northern (tRNA) gel blot and Northern (total cellular RNA) slot-blot analyses using the trnL gene probe in 6-day old etiolated cucumber seedlings and the seedlings that had been kept in the dark (dark-grown), treated with benzyladenine (BA) and kept in the dark (BA-treated dark-grown), illuminated (light-grown), and treated with BA and illuminated (BA-treated light-grown), for additional 4, 8 or 12 hr. The trnL transcripts and tRNA(Leu) levels in BA-treated dark-grown seedlings were 5 and 3 times higher, respectively after 4 hr BA treatment, while in the BA treated light-grown seedlings the level of trnL transcripts was only 3 times higher and had no detectable effect on mature tRNA(Leu) when compared to the time-4 hr dark-grown seedlings. However, the level of mature tRNA(Leu) did not show marked changes in the light-grown seedlings, whereas the level of trnL transcripts increases 3 times after 8 hr illumination of dark-grown seedlings. These data indicate that both light and cytokinin can signal changes in plastid tRNA gene expression. The possible regulatory mechanisms for such changes are discussed.

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The nucleotide sequence of a 714 bp BamHI-EcoRI fragment of cucumber chloroplast DNA was determined. The fragment contained a gene for tRNA(Leu) together with its flanking regions. The trnL(CAA) gene sequence is about 99% in similarity to broad bean, cauliflower, maize, spinach and tobacco corresponding genes. The relative expression level of the gene was determined by Northern (tRNA) gel blot and Northern (total cellular RNA) slot-blot analyses using the trnL gene probe in 6-day old etiolated cucumber seedlings and the seedlings that had been kept in the dark (dark-grown), treated with benzyladenine (BA) and kept in the dark (BA-treated dark-grown), illuminated (light-grown), and treated with BA and illuminated (BA- treated light-grown), for additional 4, 8 or 12 hr. The trnL transcripts and tRNA(Leu) levels in BA-treated dark-grown seedlings were 5 and 3 times higher, respectively after 4 hr BA treatment, while in the BA treated light-grown seedlings the level of trnL transcripts was only 3 times higher and had not detectable effect on mature tRNA(Leu) when compared to the time-4 hr dark-grown seedlings. However, the level of mature tRNA(Leu) did not show marked changes in the light-grown seedlings, whereas the level of trnL transcripts increases 3 times after 8 hr illumination of dark-grown seedlings. These date indicate that both light and cytokinin can signal changes in plastid tRNA gene expression. The possible regulatory mechanisms for such changes are discussed.

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DNA topoisomerases are ubiquitous nuclear enzymes that govern the topological interconversions of DNA by transiently breaking/rejoining the phosphodiester backbone of one (type I) or both (type II) strands of the double helix. Consistent with these functions, topoisomerases play key roles in many aspects of DNA metabolism. Type II DNA topoisomerase (topo II) is vital for various nuclear processes, including DNA replication, chromosome segregation, and maintenance of chromosome structure. Topo II expression is regulated at multiple stages, including transcriptional, posttranscriptional, and posttranslational levels, by a multitude of signaling factors. Topo II is also the cellular target for a variety of clinically relevant anti-tumor drugs. Despite significant progress in our understanding of the role of topo II in diverse nuclear processes, several important aspects of topo II function, expression, and regulation are poorly understood. We have focused this review specifically on eukaryotic DNA topoisomerase II, with an emphasis on functional and regulatory characteristics.

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The influence of fructose 2,6-bisphosphate on the activation of purified swine kidney phosphofructokinase as a function of the concentration of fructose 6P, ATP and citrate was investigated. The purified enzyme was nearly completely inhibited in the presence of 2 mM ATP. The addition of 20 nM fructose 2,6-P2 reversed the inhibition and restored more than 80% of the activity. In the absence of fructose 2,6-P2 the reaction showed a sigmoidal dependence on fructose-6-phosphate. The addition of 10 nM fructose 2,6-bisphosphate decreased the K0.5 for fructose 6-phosphate from 3 mM to 0.4 mM in the presence of 1.5 mM ATP. These results clearly show that fructose 2,6-bisphosphate increases the affinity of the enzyme for fructose 6-phosphate and decreases the inhibitory effect of ATP. The extent of inhibition by citrate was also significantly decreased in the presence of fructose 2,6-phosphate. The influence of various effectors of phosphofructokinase on the binding of ATP and fructose 6-P to the enzyme was examined in gel filtration studies. It was found that kidney phosphofructokinase binds 5.6 moles of fructose 6-P per mole of enzyme, which corresponds to about one site per subunit of tetrameric enzyme. The KD for fructose 6-P was 13 microM and in the presence of 0.5 mM ATP it increased to 27 microM. The addition of 0.3 mM citrate also increased the KD for fructose 6-P to about 40 microM. AMP, 10 microM, decreased the KD to 5 microM and the addition of fructose 2,6-phosphate decreased the KD for fructose 6-P to 0.9 microM. The addition of these compounds did not effect the maximal amount of fructose 6-P bound to the enzyme, which indicated that the binding site for these compounds might be near, but was not identical to the fructose 6-P binding site. The enzyme bound a maximum of about 12.5 moles of ATP per mole, which corresponds to 3 moles per subunit. The KD of the site with the highest affinity for ATP was 4 microM, and it increased to 15 microM in the presence of fructose 2,6-bisphosphate. The addition of 50 microM fructose 1,6-bisphosphate increased the KD for ATP to 5.9 microM. AMP increased the KD to 5.9 microM whereas 0.3 mM citrate decreased the KD for ATP to about 2 microM.(ABSTRACT TRUNCATED AT 400 WORDS).

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An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

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Multielectrode neurophysiological recording and high-resolution neuroimaging generate multivariate data that are the basis for understanding the patterns of neural interactions. How to extract directions of information flow in brain networks from these data remains a key challenge. Research over the last few years has identified Granger causality as a statistically principled technique to furnish this capability. The estimation of Granger causality currently requires autoregressive modeling of neural data. Here, we propose a nonparametric approach based on widely used Fourier and wavelet transforms to estimate both pairwise and conditional measures of Granger causality, eliminating the need of explicit autoregressive data modeling. We demonstrate the effectiveness of this approach by applying it to synthetic data generated by network models with known connectivity and to local field potentials recorded from monkeys performing a sensorimotor task.

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The csrA is a carbon storage regulator gene that encodes a protein with multiple RNA interaction sites. Bacterial non-coding small RNAs like csrB, csrC and their counterparts in diverse bacterial genus are identified to control the regulatory activities of CsrA and its orthologs. An attempt has been made in this study to identify 'novel' non-coding small RNAs that are involved in the regulatory activities of csrA gene. All CsrA-interacting small RNAs are computationally fingerprinted to have multiple occurrence of 7-nucleotide CsrA interacting repeats [CAGGA(U/A/C)G] along with a 18-nucleotide upstream binding site. However, in several of the genomes like Haemophilus spp, the upstream binding site is not identified. The current methodology overcomes this difficulty by identifying small RNA-specific orphan transcriptional units within the intergenic regions of the genome. The results could identify all known CsrA-interacting small RNAs in E. coli, Vibrio cholerae and Pseudomonas aeruginosa genomes and additionally has picked six new possible CsrA-interacting small RNA regions in E. coli. Our computational analysis indicates that known rygD and rprA sRNAs in E. coli could possibly interact with CsrA proteins. The study is extended to three of the Haemophilus genomes that could identify seven new possible CsrA interacting small RNAs.

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We consider a single-hop data-gathering sensor network, consisting of a set of sensor nodes that transmit data periodically to a base-station. We are interested in maximizing the lifetime of this network. With our definition of network lifetime and the assumption that the radio transmission energy consumption forms the most significant portion of the total energy consumption at a sensor node, we attempt to enhance the network lifetime by reducing the transmission energy budget of sensor nodes by exploiting three system-level opportunities. We pose the problem of maximizing lifetime as a max-min optimization problem subject to the constraint of successful data collection and limited energy supply at each node. This turns out to be an extremely difficult optimization to solve. To reduce the complexity of this problem, we allow the sensor nodes and the base-station to interactively communicate with each other and employ instantaneous decoding at the base-station. The chief contribution of the paper is to show that the computational complexity of our problem is determined by the complex interplay of various system-level opportunities and challenges.

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We propose a solution based on message passing bipartite networks, for deep packet inspection, which addresses both speed and memory issues, which are limiting factors in current solutions. We report on a preliminary implementation and propose a parallel architecture.