884 resultados para nuclear localization sequence recognition (NLS recognition)
Resumo:
Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts especially for the South Indian scripts. This paper provides an overview of offline handwritten character recognition in South Indian Scripts, namely Malayalam, Tamil, Kannada and Telungu
Resumo:
This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective
Resumo:
Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification
Resumo:
In this paper, we propose a handwritten character recognition system for Malayalam language. The feature extraction phase consists of gradient and curvature calculation and dimensionality reduction using Principal Component Analysis. Directional information from the arc tangent of gradient is used as gradient feature. Strength of gradient in curvature direction is used as the curvature feature. The proposed system uses a combination of gradient and curvature feature in reduced dimension as the feature vector. For classification, discriminative power of Support Vector Machine (SVM) is evaluated. The results reveal that SVM with Radial Basis Function (RBF) kernel yield the best performance with 96.28% and 97.96% of accuracy in two different datasets. This is the highest accuracy ever reported on these datasets
Resumo:
Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.
Resumo:
Development of Malayalam speech recognition system is in its infancy stage; although many works have been done in other Indian languages. In this paper we present the first work on speaker independent Malayalam isolated speech recognizer based on PLP (Perceptual Linear Predictive) Cepstral Coefficient and Hidden Markov Model (HMM). The performance of the developed system has been evaluated with different number of states of HMM (Hidden Markov Model). The system is trained with 21 male and female speakers in the age group ranging from 19 to 41 years. The system obtained an accuracy of 99.5% with the unseen data
Resumo:
A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.
Resumo:
A primary medium for the human beings to communicate through language is Speech. Automatic Speech Recognition is wide spread today. Recognizing single digits is vital to a number of applications such as voice dialling of telephone numbers, automatic data entry, credit card entry, PIN (personal identification number) entry, entry of access codes for transactions, etc. In this paper we present a comparative study of SVM (Support Vector Machine) and HMM (Hidden Markov Model) to recognize and identify the digits used in Malayalam speech.
Resumo:
The objective of the study is to develop a hand written character recognition system that could recognisze all the characters in the mordern script of malayalam language at a high recognition rate
Resumo:
This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction method has been adopted-a combination of context bitmap and normalized (x, y) coordinates. The system reported an accuracy of 88.75% which is writer independent with a recognition time of 15-32 milliseconds
Resumo:
RNA interference (RNAi) is a recently discovered process, in which double stranded RNA (dsRNA) triggers the homology-dependant degradation of cognate messenger RNA (mRNA). In a search for new components of the RNAi machinery in Dictyostelium, a new gene was identified, which was called helF. HelF is a putative RNA helicase, which shows a high homology to the helicase domain of Dicer, to the helicase domain of Dictyostelium RdRP and to the C. elegans gene drh-1, that codes for a dicer related DExH-box RNA helicase, which is required for RNAi. The aim of the present Ph.D. work was to investigate the role of HelF in PTGS, either induced by RNAi or asRNA. A genomic disruption of the helF gene was performed, which resulted in a distinct mutant morphology in late development. The cellular localization of the protein was elucidated by creating a HelF-GFP fusion protein, which was found to be localized in speckles in the nucleus. The involvement of HelF in the RNAi mechanism was studied. For this purpose, RNAi was induced by transformation of RNAi hairpin constructs against four endogenous genes in wild type and HelF- cells. The silencing efficiency was strongly enhanced in the HelF K.O. strain in comparison with the wild type. One gene, which could not be silenced in the wild type background, was successfully silenced in HelF-. When the helF gene was disrupted in a secondary transformation in a non-silenced strain, the silencing efficiency was strongly improved, a phenomenon named here “retrosilencing”. Transcriptional run-on experiments revealed that the enhanced gene silencing in HelF- was a posttranscriptional event, and that the silencing efficiency depended on the transcription levels of hairpin RNAs. In HelF-, the threshold level of hairpin transcription required for efficient silencing was dramatically lowered. The RNAi-mediated silencing was accompanied by the production of siRNAs; however, their amount did not depend on the level of hairpin transcription. These results indicated that HelF is a natural suppressor of RNAi in Dictyostelium. In contrast, asRNA mediated gene silencing was not enhanced in the HelF K.O, as shown for three tested genes. These results confirmed previous observations (H. Martens and W. Nellen, unpublished) that although similar, RNAi and asRNA mediated gene silencing mechanisms differ in their requirements for specific proteins. In order to characterize the function of the HelF protein on a molecular level and to study its interactions with other RNAi components, in vitro experiments were performed. Besides the DEAH-helicase domain, HelF contains a double-stranded RNA binding domain (dsRBD) at its N-terminus, which showed high similarity to the dsRBD domain of Dicer A from Dictyostelium. The ability of the recombinant dsRBDs from HelF and Dicer A to bind dsRNA was examined and compared. It was shown by gel-shift assays that both HelF-dsRBD and Dicer-dsRBD could bind directly to long dsRNAs. However, HelF-dsRBD bound more efficiently to dsRNA with imperfect matches than to perfect dsRNA. Both dsRBDs bound specifically to a pre-miRNA substrate (pre-let-7). The results suggested that most probably there were two binding sites for the proteins on the pre-miRNA substrate. Moreover, it was shown that HelF-dsRBD and Dicer-dsRBD have siRNA-binding activity. The affinities of the two dsRBDs to the pre-let-7 substrate were also examined by plasmon surface resonance analyses, which revealed a 9-fold higher binding affinity of the Dicer-dsRBD to pre-let-7 compared to that of the HelF-dsRBD. The binding of HelF-dsRBD to the pre-let-7 was impaired in the presence of Mg2+, while the Dicer-dsRBD interaction with pre-let-7 was not influenced by the presence of Mg2+. The results obtained in this thesis can be used to postulate a model for HelF function. In this, HelF acts as a nuclear suppressor of RNAi in wild type cells by recognition and binding of dsRNA substrates. The protein might act as a surveillance system to avoid RNAi initiation by fortuitous dsRNA formation or low abundance of dsRNA trigger. If the protein acts as an RNA helicase, it could unwind fold-back structures in the nucleus and thus lead to decreased RNAi efficiency. A knock-out of HelF would result in initiation of the RNAi pathway even by low levels of dsRNA. The exact molecular function of the protein in the RNAi mechanism still has to be elucidated. RNA interferenz (RNAi) ist ein in jüngster Zeit entdeckter Mechanismus, bei dem doppelsträngige RNA Moleküle (dsRNA) eine Homologie-abhängige Degradation einer verwandten messenger-RNA (mRNA) auslösen. Auf der Suche nach neuen Komponenten der RNAi-Maschinerie in Dictyostelium konnte ein neues Gen (helF) identifiziert werden. HelF ist eine putative RNA-Helikase mit einer hohen Homologie zur Helikasedomäne der bekannten Dicerproteine, der Helikasedomäne der Dictyostelium RdRP und zu dem C. elegans Gen drh-1, welches für eine Dicer-bezogene DExH-box RNA Helikase codiert, die am RNAi-Mechanismus beteiligt ist. Das Ziel dieser Arbeit war es, die Funktion von HelF im Zusammenhang des RNAi oder asRNA induzierten PTGS zu untersuchen. Es wurde eine Unterbrechung des helF-Gens auf genomischer Ebene (K.O.) vorgenommen, was bei den Mutanten zu einer veränderten Morphologie in der späten Entwicklung führte. Die Lokalisation des Proteins in der Zelle konnte mit Hilfe einer GFP-Fusion analysiert werden und kleinen Bereichen innerhalb des Nukleus zugewiesen werden. Im Weiteren wurde der Einfluss von HelF auf den RNAi-Mechanismus untersucht. Zu diesem Zweck wurde RNAi durch Einbringen von RNAi Hairpin-Konstrukten gegen vier endogene Gene im Wiltypstamm und der HelF--Mutante induziert. Im Vergleich zum Wildtypstamm konnte im HelF--Mutantenstamm eine stark erhöhte „Silencing“-Effizienz nachgewiesen werden. Ein Gen, welches nach RNAi Initiation im Wildtypstamm unverändert blieb, konnte im HelF--Mutantenstamm erfolgreich stillgelegt werden. Durch sekundäres Einführen einer Gendisruption im helF-Locus in einen Stamm, in welchem ein Gen nicht stillgelegt werden konnte, wurde die Effizienz des Stilllegens deutlich erhöht. Dieses Phänomen wurde hier erstmals als „Retrosilencing“ beschrieben. Mit Hilfe von transkriptionellen run-on Experimenten konnte belegt werden, dass es sich bei dieser erhöhten Stilllegungseffizienz um ein posttranskriptionelles Ereignis handelte, wobei die Stillegungseffizienz von der Transkriptionsstärke der Hairpin RNAs abhängt. Für die HelF--Mutanten konnte gezeigt werden, dass der Schwellenwert zum Auslösen eines effizienten Stillegens dramatisch abgesenkt war. Obwohl die RNAi-vermittelte Genstilllegung immer mit der Produktion von siRNAs einhergeht, war die Menge der siRNAs nicht abhängig von dem Expressionsniveau des Hairpin-Konstruktes. Diese Ergebnisse legen nahe, dass es sich bei der HelF um einen natürlichen Suppressor des RNAi-Mechanismus in Dictyostelium handelt. Im Gegensatz hierzu war die as-vermittelte Stilllegung von drei untersuchten Genen im HelF-K.O. im Vergleich zum Wildyp unverändert. Diese Ergebnisse bestätigten frühere Beobachtungen (H. Martens und W. Nellen, unveröffentlicht), wonach die Mechanismen für RNAi und asRNA-vermittelte Genstilllegung unterschiedliche spezifische Proteine benötigen. Um die Funktion des HelF-Proteins auf der molekularen Ebene genauer zu charakterisieren und die Interaktion mit anderen RNAi-Komponenten zu untersuchen, wurden in vitro Versuche durchgeführt. Das HelF-Protein enthält, neben der DEAH-Helikase-Domäne eine N-terminale Doppelstrang RNA bindende Domäne (dsRBD) mit einer hohen Ähnlichkeit zu der dsRBD des Dicer A aus Dictyostelium. Die dsRNA-Bindungsaktivität der beiden dsRBDs aus HelF und Dicer A wurde analysiert und verglichen. Es konnte mithilfe von Gel-Retardationsanalysen gezeigt werden, dass sowohl HelF-dsRBD als auch Dicer-dsRBD direkt an lange dsRNAs binden können. Hierbei zeigte sich, dass die HelF-dsRBD eine höhere Affinität zu einem imperfekten RNA-Doppelstrang besitzt, als zu einer perfekt gepaarten dsRNA. Für beide dsRBDs konnte eine spezifische Bindung an ein pre-miRNA Substrat nachgewiesen werden (pre-let-7). Dieses Ergebnis legt nah, dass es zwei Bindestellen für die Proteine auf dem pre-miRNA Substrat gibt. Überdies hinaus konnte gezeigt werden, dass die dsRBDs beider Proteine eine siRNA bindende Aktivität besitzen. Die Affinität beider dsRBDs an das pre-let-7 Substrat wurde weiterhin mit Hilfe der Plasmon Oberflächen Resonanz untersucht. Hierbei konnte eine 9-fach höhere Bindeaffinität der Dicer-dsRBD im Vergleich zur HelF-dsRBD nachgewiesen werden. Während die Bindung der HelF-dsRBD an das pre-let-7 durch die Anwesenheit von Mg2+ beeinträchtigt war, zeigte sich kein Einfluß von Mg2+ auf das Bindeverhalten der Dicer-dsRBD. Mit Hilfe der in dieser Arbeit gewonnen Ergebnisse lässt sich ein Model für die Funktion von HelF postulieren. In diesem Model wirkt HelF durch Erkennen und Binden von dsRNA Substraten als Suppressor von der RNAi im Kern. Das Protein kann als Überwachungsystem gegen eine irrtümliche Auslösung von RNAi wirken, die durch zufällige dsRNA Faltungen oder eine zu geringe Häufigkeit der siRNAs hervorgerufen sein könnte. Falls das Protein eine Helikase-Aktivität besitzt, könnte es rückgefaltete RNA Strukturen im Kern auflösen, was sich in einer verringerten RNAi-Effizienz wiederspiegelt. Durch Ausschalten des helF-Gens würde nach diesem Modell eine erfolgreiche Auslösung von RNAi schon bei sehr geringer Mengen an dsRNA möglich werden. Das Modell erlaubt, die exakte molekulare Funktion des HelF-Proteins im RNAi-Mechanismus weiter zu untersuchen.
Resumo:
Cell-cell interactions during embryonic development are crucial in the co-ordination of growth, differentiation and maintenance of many different cell types. To achieve this co-ordination each cell must properly translate signals received from neighbouring cells, into spatially and temporally appropriate developmental responses. A surprisingly limited number of signal pathways are responsible for the differentiation of enormous variety of cell types. As a result, pathways are frequently 'reused' during development. Thus, in mammals the JAK/STAT pathway is required during early embryogenesis, mammary gland formation, hematopoiesis and, finally, plays a pivotal role in immune response. In the canonical way, the JAK/STAT pathway is represented by a transmembrane receptor associated with a Janus kinase (JAK), which upon stimulation by an extra-cellular ligand, phosphorylates itself, the receptor and, finally, the signal transducer and activator of transcription (STAT) molecules. Phosphorylated STATs dimerise and translocate to the nucleus where they activate transcription of target genes. The JAK/STAT pathway has been conserved throughout evolution, and all known components are present in the genome of Drosophila melanogaster. Besides hematopoietic and immunity functions, the pathway is also required during development for processes including embryonic segmentation, tracheal morphogenesis, posterior spiracle formation etc. This study describes Drosophila Ken&Barbie (Ken) as a selective regulator of JAK/STAT signalling. ken mutations identified in a screen for modulators of an eye overgrowth phenotype, caused by over-expression of the pathway ligand unpaired, also interact genetically with the pathway receptor domeless (dome) and the transcription factor stat92E. Over-expression of Ken can phenocopy developmental defects known to be caused by the loss of JAK/STAT signalling. These genetic interactions suggest that Ken may function as a negative regulator of the pathway. Ken has C-terminal Zn-finger domain, presumably for DNA binding, and N-terminal BTB/POZ domain, often found in transcriptional repressors. Using EGFP-fused construct expressed in vivo revealed nuclear accumulation of Ken. Therefore, it is proposed that Ken may act as a suppresser of STAT92E target genes. An in vitro assay, termed SELEX, determined that Ken specifically binds to a DNA sequence, with the essential for DNA recognition core overlapping that of STAT92E. This interesting observation suggests that not all STAT92E sites may also allow Ken binding. Strikingly, when effects of ectopic Ken on the expression of putative JAK/STAT pathway target genes were examined, only a subset of the genes tested, namely vvl, trh and kni, were down-regulated by Ken, whereas some others, such as eve and fj, appeared to be unresponsive. Further analysis of vvl, one of the genes susceptible to ectopic Ken, was undertaken. In the developing hindgut, expression of vvl is JAK/STAT pathway dependent, but remains repressed in the posterior spiracles, despite the stimulation of STAT92E by Upd in their primordia. Importantly, ken is also expressed in the developing posterior spiracles. Strikingly, up-regulation of vvl is observed in these tissues in ken mutant embryos. These imply that while ectopic Ken is sufficient to repress the expression of vvl in the hindgut, endogenous Ken is also necessary to prevent its activation in the posterior spiracles. It is therefore conceivable that ectopic vvl expression in the posterior spiracles of the ken mutants may be the result of de-repression of endogenous STAT92E activity. Another consequence of these observations is a fine balance that must exist between STAT92E and Ken activities. Apparently, endogenous level of Ken is sufficient to repress vvl, but not other, as yet unidentified, JAK/STAT pathway targets, whose presumable activation by STAT92E is required for posterior spiracle development as the embryos mutant for dome, the receptor of the pathway, show severe spiracle defects. These defects are also observed in the embryos mis-expressing Ken. Though it is possible that the posterior spiracle phenotype caused by higher levels of Ken results from a JAK/STAT pathway independent activity, it seems to be more likely that Ken acts in a dosage dependent manner, and extra Ken is able to further antagonise JAK/STAT pathway target genes. While STAT92E binding sites required for target gene expression have been poorly characterised, the existence of genome data allows the prediction of candidate STAT92E sites present in target genes promoters to be attempted. When a 6kb region containing the putative regulatory domains flanking the vvl locus are examined, only a single potential STAT92E binding site located 825bp upstream of the translational start can be detected. Strikingly, this site also includes a perfect Ken binding sequence. Such an in silico observation, though consistent with both Ken DNA binding assay in vitro and regulation of STAT92E target genes in vivo, however, requires further analysis. The JAK/STAT pathway is implicated in a variety of processes during embryonic and larval development as well as in imago. In each case, stimulation of the same transcription factor results in different developmental outcomes. While many potential mechanisms have been proposed and demonstrated to explain such pleiotropy, the present study indicates that Ken may represent another mechanism, with which signal transduction pathways are controlled. Ken selectively down-regulates a subset of potential target genes and so modifies the transcriptional profile generated by activated STAT92E - a mechanism, which may be partially responsible for differences in the morphogenetic processes elicited by JAK/STAT signalling during development.
Resumo:
This thesis describes the development of a model-based vision system that exploits hierarchies of both object structure and object scale. The focus of the research is to use these hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to recognize parameterized instances of non-rigid model objects contained in a large knowledge base despite the presence of noise and occlusion. Robustness is achieved by developing a system that can recognize viewed objects that are scaled or mirror-image instances of the known models or that contain components sub-parts with different relative scaling, rotation, or translation than in models. The approach taken in this thesis is to develop an object shape representation that incorporates a component sub-part hierarchy- to allow for efficient and correct indexing into an automatically generated model library as well as for relative parameterization among sub-parts, and a scale hierarchy- to allow for a general to specific recognition procedure. After analysis of the issues and inherent tradeoffs in the recognition process, a system is implemented using a representation based on significant contour curvature changes and a recognition engine based on geometric constraints of feature properties. Examples of the system's performance are given, followed by an analysis of the results. In conclusion, the system's benefits and limitations are presented.