NrichD database: sequence databases enriched with computationally designed protein-like sequences aid in remote homology detection

NrichD ( ext-link-type=''uri'' xlink:href=''http://proline.biochem.iisc.ernet.in/NRICHD/'' xlink:type=''simple''>http://proline.biochem.iisc.ernet.in/NRICHD/)< /named-content> is a database of computationally designed protein-like sequences, augmented into natural sequence databases that can perform hops in protein sequence space to assist in the detection of remote relationships. Establishing protein relationships in the absence of structural evidence or natural `intermediately related sequences' is a challenging task. Recently, we have demonstrated that the computational design of artificial intermediary sequences/linkers is an effective approach to fill naturally occurring voids in protein sequence space. Through a large-scale assessment we have demonstrated that such sequences can be plugged into commonly employed search databases to improve the performance of routinely used sequence search methods in detecting remote relationships. Since it is anticipated that such data sets will be employed to establish protein relationships, two databases that have already captured these relationships at the structural and functional domain level, namely, the SCOP database and the Pfam database, have been `enriched' with these artificial intermediary sequences. NrichD database currently contains 3 611 010 artificial sequences that have been generated between 27 882 pairs of families from 374 SCOP folds. The data sets are freely available for download. Additional features include the design of artificial sequences between any two protein families of interest to the user.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

Molecular Dissection of Mycobacterium tuberculosis Integration Host Factor Reveals Novel Insights into the Mode of DNA Binding and Nucleoid Compaction

The annotated whole-genome sequence of Mycobacterium tuberculosis indicated that Rv1388 (Mtihf) likely encodes a putative 20 kDa integration host factor (mIHF). However, very little is known about the functional properties of mIHF or organization of mycobacterial nucleoid. Molecular modeling of the mIHF three-dimensional structure, based on the cocrystal structure of Streptomyces coelicolor IHF-duplex DNA, a bona fide relative of mIHF, revealed the presence of Arg170, Arg171, and Arg173, which might be involved in DNA binding, and a conserved proline (P150) in the tight turn. The phenotypic sensitivity of Escherichia coli Delta ihfA and Delta ihfB strains to UV and methylmethanesulfonate could be complemented with the wild-type Mtihf, but not its alleles bearing mutations in the DNA-binding residues. Protein DNA interaction assays revealed that wild-type mIHF, but not its DNA-binding variants, bind with high affinity to fragments containing attB and attP sites and curved DNA. Strikingly, the functionally important amino acid residues of mIHF and the mechanism(s) underlying its binding to DNA, DNA bending, and site-specific recombination are fundamentally different from that of E. coli IHF alpha beta. Furthermore, we reveal novel insights into IHF-mediated DNA compaction depending on the placement of its preferred binding sites; mIHF promotes compaction of DNA into nucleoid-like or higher-order filamentous structures. We hence propose that mIHF is a distinct member of a subfamily of proteins that serve as essential cofactors in site-specific recombination and nucleoid organization and that these findings represent a significant advance in our understanding of the role(s) of nucleoid-associated proteins.

Active learning in keyword search-based data integration

The problem of scaling up data integration, such that new sources can be quickly utilized as they are discovered, remains elusive: Global schemas for integrated data are difficult to develop and expand, and schema and record matching techniques are limited by the fact that data and metadata are often under-specified and must be disambiguated by data experts. One promising approach is to avoid using a global schema, and instead to develop keyword search-based data integration-where the system lazily discovers associations enabling it to join together matches to keywords, and return ranked results. The user is expected to understand the data domain and provide feedback about answers' quality. The system generalizes such feedback to learn how to correctly integrate data. A major open challenge is that under this model, the user only sees and offers feedback on a few ``top-'' results: This result set must be carefully selected to include answers of high relevance and answers that are highly informative when feedback is given on them. Existing systems merely focus on predicting relevance, by composing the scores of various schema and record matching algorithms. In this paper, we show how to predict the uncertainty associated with a query result's score, as well as how informative feedback is on a given result. We build upon these foundations to develop an active learning approach to keyword search-based data integration, and we validate the effectiveness of our solution over real data from several very different domains.

Integrating AlGaN/GaN high electron mobility transistor with Si: A comparative study of integration schemes

AlGaN/GaN high electron mobility transistor stacks deposited on a single growth platform are used to compare the most common transition, AlN to GaN, schemes used for integrating GaN with Si. The efficiency of these transitions based on linearly graded, step graded, interlayer, and superlattice schemes on dislocation density reduction, stress management, surface roughness, and eventually mobility of the 2D-gas are evaluated. In a 500 nm GaN probe layer deposited, all of these transitions result in total transmission electron microscopy measured dislocations densities of 1 to 3 x 10(9)/cm(2) and <1 nm surface roughness. The 2-D electron gas channels formed at an AlGaN-1 nm AlN/GaN interface deposited on this GaN probe layer all have mobilities of 1600-1900 cm(2)/V s at a carrier concentration of 0.7-0.9 x 10(13)/cm(2). Compressive stress and changes in composition in GaN rich regions of the AlN-GaN transition are the most effective at reducing dislocation density. Amongst all the transitions studied the step graded transition is the one that helps to implement this feature of GaN integration in the simplest and most consistent manner. (C) 2015 AIP Publishing LLC.

Network integration for international mergers and Acquisitions

Business activities are increasingly taking place across geographical and ownership boundaries. Post-Merger & Acquisition Integration (PMI) processes are more challenging in network organisations due to the extra complexity and interdependency associated with networks. However, network integration issues are not well addressed in the traditional M&A literature or the network organisation literature. Based on ten in-depth case studies across key industry sectors, this research identifies the essential network integration issues for international M&As with a configuration concept, and demonstrates different network integration patterns according to M&A objectives for growth and efficiency. This paper extends the theoretical understanding of PMI for network organisations. It can also provide practical guidance for managers to assess the feasibility of an M&A transition or to go through the PMI process successfully. Copyright © 2010 Inderscience Enterprises Ltd.

A comparative study of plasma-enhanced chemical vapor gate dielectrics for solution-processed polymer thin-film transistor circuit integration

This paper considers plasma-enhanced chemical vapor deposited (PECVD) silicon nitride (SiNx) and silicon oxide (SiOx) as gate dielectrics for organic thin-film transistors (OTFTs), with solution-processed poly[5, 5′ -bis(3-dodecyl-2-thienyl)-2, 2′ -bithiophene] (PQT-12) as the active semiconductor layer. We examine transistors with SiNx films of varying composition deposited at 300 °C as well as 150 °C for plastic compatibility. The transistors show over 100% (two times) improvement in field-effect mobility as the silicon content in SiNx increases, with mobility (μFE) up to 0.14 cm2 /V s and on/off current ratio (ION / IOFF) of 108. With PECVD SiOx gate dielectric, preliminary devices exhibit a μFE of 0.4 cm2 /V s and ION / IOFF of 108. PQT-12 OTFTs with PECVD SiNx and SiOx gate dielectrics on flexible plastic substrates are also presented. These results demonstrate the viability of using PECVD SiN x and SiOx as gate dielectrics for OTFT circuit integration, where the low temperature and large area deposition capabilities of PECVD films are highly amenable to integration of OTFT circuits targeted for flexible and lightweight applications. © 2008 American Institute of Physics.

Integration of holographic sensors into microfluidics for the real-time pH sensing of L. casei metabolism

We describe developments in the integration of analyte specific holographic sensors into PDMS-based microfluidic devices for the purpose of continuous, low-impact monitoring of extra-cellular change in micro-bioreactors. Holographic sensors respond to analyte concentration via volume change, which makes their reduction in size and integration into spatially confined fluidics difficult. Through design and process modification many of these constraints have been addressed, and a microfluidics-based device capable of real-time monitoring of the pH change caused by Lactobacillus casei fermentation is presented as a general proof-of-concept for a wide array of possible devices.

Coarse-to-fine vision-based localization by indexing scale-invariant features

This paper presents a novel coarse-to-fine global localization approach inspired by object recognition and text retrieval techniques. Harris-Laplace interest points characterized by scale-invariant transformation feature descriptors are used as natural landmarks. They are indexed into two databases: a location vector space model (LVSM) and a location database. The localization process consists of two stages: coarse localization and fine localization. Coarse localization from the LVSM is fast, but not accurate enough, whereas localization from the location database using a voting algorithm is relatively slow, but more accurate. The integration of coarse and fine stages makes fast and reliable localization possible. If necessary, the localization result can be verified by epipolar geometry between the representative view in the database and the view to be localized. In addition, the localization system recovers the position of the camera by essential matrix decomposition. The localization system has been tested in indoor and outdoor environments. The results show that our approach is efficient and reliable. © 2006 IEEE.