Дисертації з теми "Snakes – Classification"

BACKGROUND:The extant squamates (>9400 known species of lizards and snakes) are one of the most diverse and conspicuous radiations of terrestrial vertebrates, but no studies have attempted to reconstruct a phylogeny for the group with large-scale taxon sampling. Such an estimate is invaluable for comparative evolutionary studies, and to address their classification. Here, we present the first large-scale phylogenetic estimate for Squamata.RESULTS:The estimated phylogeny contains 4161 species, representing all currently recognized families and subfamilies. The analysis is based on up to 12896 base pairs of sequence data per species (average = 2497 bp) from 12 genes, including seven nuclear loci (BDNF, c-mos, NT3, PDC, R35, RAG-1, and RAG-2), and five mitochondrial genes (12S, 16S, cytochrome b, ND2, and ND4). The tree provides important confirmation for recent estimates of higher-level squamate phylogeny based on molecular data (but with more limited taxon sampling), estimates that are very different from previous morphology-based hypotheses. The tree also includes many relationships that differ from previous molecular estimates and many that differ from traditional taxonomy.CONCLUSIONS:We present a new large-scale phylogeny of squamate reptiles that should be a valuable resource for future comparative studies. We also present a revised classification of squamates at the family and subfamily level to bring the taxonomy more in line with the new phylogenetic hypothesis. This classification includes new, resurrected, and modified subfamilies within gymnophthalmid and scincid lizards, and boid, colubrid, and lamprophiid snakes.

Active contours have been proven to be a powerful semiautomatic image segmentation approach, that seems to cope with many applications and different image modalities. However, they exhibit inherent drawbacks, including the sensibility to contour initialization due to the limited capture range of image edges and problems with concave boundary regions. The Gradient Vector Flow replaces the traditional image force and provides an enlarged capture range as well as enhanced concavity extraction capabilities, but it involves an expensive computational effort and considerably increased memory requirements at the time of computation. In this paper, we present an enhancement of the active contour model to facilitate semiautomatic contour detection in huge images. We propose a tile-based image decomposition accompanying an image force computation scheme on demand in order to minimize both computational and memory requirements. We show an efficient implementation of this approach on the basis of general purpose GPU processing providing for continuous active contour deformation without a considerable delay.

Die vorliegende Arbeit befasst sich mit Algorithmen aus dem Bereich der Bildsegmentierung sowie der Datensynthese für das so genannte Hologrammdruck-Prinzip. Angelehnt an ein anatomisch motiviertes Forschungsprojekt werden aktive Konturen zur halbautomatischen Segmentierung digitalisierter histologischer Schnitte herangezogen. Die besondere Herausforderung liegt dabei in der Entwicklung von verschiedenen Ansätzen, die der Anpassung des Verfahrens für sehr große Bilder dienen, welche in diesem Kontext eine Größe von einigen hundert Megapixel erreichen können. Unter dem Aspekt der größtmöglichen Effizienz, jedoch mit der Beschränkung auf die Verwendung von Consumer-Hardware, werden Ideen vorgestellt, welche eine auf aktiven Konturen basierende Segmentierung bei derartigen Bildgrößen erstmals ermöglichen sowie zur Beschleunigung und Reduktion des Speicheraufwandes beitragen. Darüber hinaus wurde das Verfahren um ein intuitives Werkzeug erweitert, das eine interaktive lokale Korrektur der finalen Kontur gestattet und damit die Praxistauglichkeit der Methode maßgeblich erhöht. Der zweite Teil der Arbeit beschäftigt sich mit einem Druckprinzip für die Herstellung von Hologrammen, basierend auf virtuellen Abbildungsgegenständen. Der Hologrammdruck, der namentlich an die Arbeitsweise eines Tintenstrahldruckers erinnern soll, benötigt dazu spezielle diskrete Bilddaten, die als Elementarhologramme bezeichnet werden. Diese tragen die visuelle Information verschiedener Blickrichtungen durch einen festen geometrischen Ort auf der Hologrammebene. Ein vollständiges, aus vielen Elementarhologrammen zusammengesetztes Hologramm erzeugt dabei ein erhebliches Datenvolumen, das parameterabhängig schnell im Terabyte-Bereich liegen kann. Zwei unabhängige Algorithmen zur Erzeugung geeignet aufbereiteter Daten unter intensiver Ausnutzung von Standard-Graphikhardware werden präsentiert, hinsichtlich ihrer Berechnungs- sowie Speicherkomplexität verglichen und unter Berücksichtigung von Qualitätsaspekten bewertet.

The development of computer algorithms for music instrument identification and parameter extraction in digital audio signals is an active research field. A musician can listen to music and instantly identify different instruments and the timbres produced by various playing techniques. Creating software to allow computers to do the same is much more challenging. This thesis will use digital signal processing and machine learning techniques to differentiate snare drum timbres produced by different stroke positions and stroke techniques.

Understanding irrigator responses to previous changes in water availability is critical to building effective institutions that allow for efficient and resilient management of water resources in the face of potentially increasing scarcity due to climate change. Using remote sensing data, I examined irrigator responses to seasonal changes in water availability in Idaho's Snake River Plain over the past 33 years. Google Earth Engine's high performance cloud computing and big data processing capabilities were used to compare the performance of three spectral indices, three compositing algorithms and two sensors for 2002 and 2007 for distinguishing between irrigated and non-irrigated parcels. We demonstrate that, on average, the seasonal-maximum algorithm yields a 60% reduction in county scale root mean square error (RMSE) over the accepted single-date approach. We use the best performing classification method, a binary threshold of the seasonal maximum of the Normalized Difference Moisture Index (NDMI), to identify irrigated and non-irrigated lands in Idaho's Snake River Basin for 1984-2016 using Landsat 5-8 data. NDMI of irrigated lands was found to generally increase over time, likely as a result of changes in agricultural practices increasing crop productivity. Furthermore, we find that irrigators with rights to small areas, and those with only surface water rights are more likely to have a major reduction (>25%) in irrigated area and conversely those with a large, groundwater rights are more likely to have major increases (>25%) in the extent of their irrigation.
Master of Science

Two discreet methods of geometric morphometrics were applied to evaluate the taxonomic utility of each in classifying the craniomandibular region of several Mustela species. Use of both linear measurements and 2-dimensional landmarks proved successful in discriminating between extant M. nigripes (black-footed ferret) and Neovison vison (American mink), in addition to the extant North American weasel species (M. erminea, M. frenata, M. nivalis). Methods were then used to classify Late Pleistocene Mustela spp. fossils collected from Snake Creek Burial Cave (SCBC) of eastern Nevada. Data acquired for unknown predicted group memberships varied markedly among methods and specimens. Nevertheless, results support the presence of M. nigripes and all 3 weasel taxa among the SCBC paleofauna.

Le développement de méthodes de la détection en temps réel de cellules anormales (pouvant être considérées comme des cellules cancéreuses) par captures et traitements bio-images sont des axes de recherche importants dans le domaine biomédical car cela contribue à diagnostiquer un cancer. C’est dans ce contexte que se situe ces travaux de thèse. Plus précisément, les travaux présentés dans ce manuscrit, se focalise sur le développement de procédures de lecture, de détection et de classification automatiques de bio-images de cellules anormales considérées comme des cellules cancéreuses. Par conséquent, une première étape du travail à consister à déterminer une solution de détection, à partir d’images microscopiques multispectrales permettant une répétitivité d’images sur une gamme de longueurs d'ondes de certains types de bio-images anormales associées à différents stades ou évolutions de cellules cancéreuses. L’approche développée dans ces travaux repose sur l’exploitation d’une nouvelle méthode de segmentation basée sur l'intensité de la couleur et pouvant être appliquée sur des séquences d'objets dans une image en reformant de manière adaptative et itérative la localisation et la couverture de contours réels de cellules. Cette étape préalable de segmentation est primordiale et permet une classification des tissus anormaux en utilisant la méthode de réseau de neurones à convolution (CNN) appliqué sur les images microscopiques segmenté de type snake. L’approche permet d’obtenir de bas résultats comparativement à une approche basée sur d’autres méthodes de segmentation de la littérature. En effet, cette méthode de classification atteint des valeurs de performance de 100% pour la phase d’apprentissage et de 99.168 % pour les phases de test. Cette méthode est comparée à différents travaux antérieurs et basée sur différentes fonctionnalités d'extraction, et a prouvé son efficacité par rapport à ces autres méthodes. En terme de perspectives, les travaux futurs visent à valider notre approche sur des ensembles de données plus larges, et à explorer différentes architectures CNN selon différents critères d’optimisation
Development of methods for help diagnosis of the real time detection of abnormal cells (which can be considered as cancer cells) through bio-image processing and detection are most important research directions in information science and technology. Our work has been concerned by developing automatic reading procedures of the normal and abnormal bio-images tissues. Therefore, the first step of our work is to detect a certain type of abnormal bio-images associated to many types evolution of cancer within a Microscopic multispectral image, which is an image, repeated in many wavelengths. And using a new segmentation method that reforms itself in an iterative adaptive way to localize and cover the real cell contour, using some segmentation techniques. It is based on color intensity and can be applied on sequences of objects in the image. This work presents a classification of the abnormal tissues using the Convolution neural network (CNN), where it was applied on the microscopic images segmented using the snake method, which gives a high performance result with respect to the other segmentation methods. This classification method reaches high performance values, where it reaches 100% for training and 99.168% for testing. This method was compared to different papers that uses different feature extraction, and proved its high performance with respect to other methods. As a future work, we will aim to validate our approach on a larger datasets, and to explore different CNN architectures and the optimization of the hyper-parameters, in order to increase its performance, and it will be applied to relevant medical imaging tasks including computer-aided diagnosis

A study of the Helminthoglyptidae of Sonora was undertaken to determine the extent of their distribution and speciation. As a result, nine new species of Sonorella are described, and new ranges of the known species are given. The status of the family is reviewed and its standing is supported with the analysis of morphological characteristics of several genera. The zoogeography of the family and its distribution are shown. Possible dispersal and isolation mechanisms are discussed in order to explain the present distribution of these snails, and comments on ecological and speciation accounts are offered.

This diploma thesis describes how to create or convert traditional Java programs to desktop-like rich internet applications with the Google Web Toolkit. The Google Web Toolkit is an open source development environment, which translates Java code to browser and device independent HTML and JavaScript. Most of the GWT framework parts, including the Java to JavaScript compiler as well as important security issues of websites will be introduced. The famous Agricola board game will be implemented in the Model-View-Presenter pattern to show that complex user interfaces can be created with the Google Web Toolkit. The Google Web Toolkit framework will be compared with the JavaServer Faces one to find out which toolkit is the right one for the next web project
Diese Diplomarbeit beschreibt die Erzeugung desktopähnlicher Anwendungen mit dem Google Web Toolkit und die Umwandlung klassischer Java-Programme in diese. Das Google Web Toolkit ist eine Open-Source-Entwicklungsumgebung, die Java-Code in browserunabhängiges als auch in geräteübergreifendes HTML und JavaScript übersetzt. Vorgestellt wird der Großteil des GWT Frameworks inklusive des Java zu JavaScript-Compilers sowie wichtige Sicherheitsaspekte von Internetseiten. Um zu zeigen, dass auch komplizierte graphische Oberflächen mit dem Google Web Toolkit erzeugt werden können, wird das bekannte Brettspiel Agricola mittels Model-View-Presenter Designmuster implementiert. Zur Ermittlung der richtigen Technologie für das nächste Webprojekt findet ein Vergleich zwischen dem Google Web Toolkit und JavaServer Faces statt

This thesis reviews the species level systematics of Pseudonaja, a group of medically important hydrophiine snakes, commonly called brown snakes.
Thesis (M.Sc.) -- University of Adelaide, School of Earth and Environmental Sciences, 2003

碩士
華梵大學
環境與防災設計學系碩士班
94
Due to highly disturbances from human developments, wetlands that are rich in ecological values are being destroyed and the number of related organisms is reduced. Analyzing the sensitive species and their habitat can improvement not only the understandings of how those sensitive species choose their microhabitat but also reflect minor changes of the environment resulting from human disturbances, hence, achieves the goal of monitoring environmental changes. This research used the semi-aquatic snakes’ survey data and the aquatic microhabitat factors to analyze the spatial distribution and the micro-habitat selection of semi-aquatic snakes. We also estimated the benefit of using multi-spectral images in aquatic microhabitat classification. Study area was located in Tau-Yuan County, where two kinds of funnel traps were set up in bogs and ponds. A total of 105 funnel traps including 15 sinking funnel traps and 90 floating funnel traps were used for capture of semi-aquatic snakes. From Sep. 2004 to Sep. 2005, a total of 49 male and 34 female Xenochrophis piscator, a total of 181 individuals, were captured. And 33 male and 36 female Sinonatrix annularis, a total of 118 individuals, were captured. Physical microhabitat factors such as water depth, mud thickness, aquatic vegetation coverage, canopy closure, grass height were measured 1 m2 around traps. The geographic information system (GIS) were used to calculate disturbance factors such as distance to lands, distance to shores, distance to houses, distance to roads, and distance to farmlands. The multivariate analyses were conducted to understand the relationship between these ten microhabitat factors and semi-aquatic snakes’ appearance frequency. Results showed that in the ponds, water depth, aquatic vegetation coverage, and distance to houses were the main microhabitat factors for X. piscator, and water depth and canopy closure were the main factors for S. annularis. In bogs, canopy closure and distance to houses were the main factors that influenced X. piscator’s microhabitat selection and water depth and distance to houses were the main factors that influenced S. annularis’s habitat selection. If the two habitat types were combined, only water depth was highly related to the appearance frequencies of the two surveyed semi-aquatic snakes. Therefore, the water depth alone was used to classify microhabitat types for ponds. Two algorisms, i.e., the maximum likely hood and minimum distance, were used for supervised classifications of multi-spectral images. The classification result showed that when few spatial pixels were available, the maximum likely hood cannot be performed. The overall accuracy of minimum distance was 70%. Different water depths were successfully classified into classes such as shallow water (water depth under 30cm), middle water (water depth 30cm~60cm), and deep water (90cm~120cm) with accuracies of 66.67%, 85.71% and 100%, respectively. Overall, the depth of water was the main microhabitat factor for both X. piscator and S. annularis in wetland habitat as a whole. Canopy coverage and aquatic vegetation may have played a minor role in microhabitat selection for X. piscator and S. annularis in different area. Both X. piscator and S. annularis appeared in the same location but may have occupied different depth of water. The human disturbances may have decreased X. piscator but increase S. annularis population. If the water depth were to be used as the major microhabitat classification factor, the multi-spectral images can be used to classify area microhabitat successfully.

Eukaryotic cells are populated by membrane-enclosed organelles possessing discrete molecular and biochemical properties. Communication between organelles is established by shuttling vesicles that transport proteins and other molecules. Vesicles bud from a donor organelle, travel in the cytosol, and are delivered to a target organelle. All these steps are regulated to ensure that cargoes are transported in a specific and directed manner. The focus of this thesis is on the last part of the journey of a vesicle: the process of vesicle targeting. Two phases can be distinguished in this process: vesicle tethering, defined as the first interaction between the shuttling vesicle and the target membrane, and membrane fusion, which is the mixing of the lipid bilayers and of lumen content. Both phases are mediated by a minimal set of molecular components that include one member of the family of Rab GTPases, a vesicle tethering factor, a phosphoinositide lipid, and four SNAREs together with their regulatory proteins. While many studies have investigated the molecular details of how SNAREs mediate membrane fusion, the process of vesicle tethering is less well understood. The overall scope of my study is to describe the molecular details of vesicle tethering and how they can contribute to the general process of vesicle targeting. To address this question I developed an in vitro assay where I reconstitute in vitro the process of vesicle tethering. This bottom-up approach allows the molecular dissection of cellular processes outside of the complex context of the cell. With this assay I have characterized the vesicle tethering abilities of individual proteins involved in vesicle tethering on early endosomes. I show that a minimal vesicle tethering machinery can be formed by the concomitant interaction between one vesicle tethering factor and a phosphoinositide on the membrane of one vesicle, and by a vesicle tethering factor and a Rab GTPase on the membrane of another vesicle. These results provide an explanation for how vesicle tethering contributes to the specificity of vesicle targeting and to the directionality of cargo transport. In particular, specificity of vesicle targeting can arise from the specific interaction between a Rab and a vesicle tethering factor that is an effector of the Rab. I show that the asymmetric distribution of binding sites in the structure of a vesicle tethering factor can generate a heterotypic vesicle tethering reaction that can account for the directionality of cargo transport. The outcome of this thesis emphasizes the role that vesicle tethering factors have in the self-organized system of vesicle trafficking of eukaryotic cells. To identify novel Rab5 effectors implicated in vesicle tethering, I carried out a Rab5-chromatography on mouse liver. Amongst other novel Rab5 effectors, I identify a multi-subunit vesicle tethering complex that was not previously characterized in mammalian cells. The complex, named CORVET, is conserved from yeast to humans and plays a major role in cell physiology since its removal causes embryonic death in mice. I define its subunits composition, determine its subcellular localization, and elucidate its role in cargo transport. This finding reconciles a disharmony between findings in mammals and yeast regarding the molecular machinery responsible for the conversion from early to late endosomes. I also show that the newly identified subunit of the mammalian CORVET complex is the only Rab5 effector to localize to autophagosomes. I hypothesise that it is through the CORVET complex that Rab5 is involved in the formation and maturation of autophagosomes.

In der vorliegenden Arbeit sollte die Eignung von T. pyriformis GL für den Nachweis von Botulinumneurotoxinen als biologische Alternative zum Maus-Bioassay untersucht werden. Dazu wurden funktionelle Tests für die Quantifizierung der mutmaßlich SNARE-abhängigen Prozesse Phagozytose und Exozytose entwickelt. Die Botulinumneurotoxine wurden durch Kultivierung der C. botulinum-Toxovare A bis G in einem Caseinpepton-Glukose-Hefeextrakt-Medium mit und ohne Zusatz von Trypsin herge-stellt. Die Neurotoxinkonzentrationen wurden mit Hilfe des Maus-Bioassays bestimmt. Für den Phagozytosetest wurde E. coli K12 als Beutekeim gewählt. Es konnte gezeigt werden, dass die KbE/ml von E. coli K12 allein durch die Phagozytoseaktivität von T. pyriformis reduziert wurde. Für den Exozytosetest wurde die saure Phosphatase als Leitenzym gewählt. Die neurotoxinhaltigen Kulturüberstände wurden mit Neurotoxinendkonzentrationen von 1,50E+02 MLD/ml (Maus letale Dosis/ml) bei den trypsinisierten und nicht trypsinisierten Ansätzen der Toxovare A bis D, F und G bzw. von 1,50E+00 MLD/ml bei dem trypsinisierten Ansatz des Toxovars E in den entwickelten Tests eingesetzt und auf ihren Einfluss untersucht. Die eingesetzten Neurotoxinkonzentrationen erwiesen sich als nicht ausreichend. Zudem wurde eine erhebliche Anfälligkeit der Phagozytose- und Exozytoseleistung von T. pyriformis gegen die Proteinkonzentrationen der eingesetzten Kulturüberstände nachgewiesen. Aufgrund dessen ist die Eignung von T. pyriformis im Rahmen der entwickelten Tests für den Nachweis von Botulinumneurotoxinen aus Proben wie biologischen Substraten oder mit ähnlichen, komplexen Matrizes nicht gegeben.

Venomous animals have evolved a vast array of peptide toxins for prey capture and defense. Nature has evolved the venoms into a huge library of active molecules with high selectivity and affinity, which could be explored as therapeutics or serve as a template for drug design. The individual components of venom i.e. toxins are used in ion channel and receptor studies, drug discovery, and formulation of insecticides. ‘Venominformatics is a systematic bioinformatics approach in which classified, consolidated and cleaned venom data are stored into repositories and integrated with advanced bioinformatics tools and computational biology for the analysis of structure and function of toxins.’ Conus peptides (conopeptides), the main components of Conus venom, represent a unique arsenal of neuropharmacologically active molecules that have been evolutionarily tailored to afford unprecedented and exquisite selectivity for a wide variety of ion-channel subtypes and neuronal receptors. Ziconotide (ω-conotoxin MVIIa from Conus magus (Magician's cone snail)), is proven as an intrathecally administered N-type calcium channel antagonist for the treatment of chronic pain (U.S. Food and Drug Administration. Center for Drug Evaluation and Research) attesting to the pharmaceutical importance of Conus peptides. From the point of view of protein sequence and structure analysis, conopeptides can serve as attractive systems for the studies in sequence comparison, pattern extraction, structure–function correlations, protein–protein interactions and evolutionary analysis. Despite their importance and extensive experimental investigations on them, they have been hardly explored through in silico methods. The present thesis is perhaps the first attempt at deploying a multi-pronged bioinformatics approaches for studies in the burgeoning field of conopeptides. In the process of sequence-structure-function studies of conopeptides, we have created several sequence patterns of different conopeptide families and these have been accepted for inclusion in international databases such as PROSITE, the first pattern database to have been developed (http://www.expasy.org/prosite) and INTERPRO (http://www.ebi.ac.uk/interpro). More importantly, we have carried out extensive literature survey on the peptides for which we have defined the patterns to create PROSITE compatible documentation files (PDOC6004, PDOC60025 and PDOC60027). We have also created a series of sequence patterns and associated documentation filesof pharmaceutically promising peptides from plants and venomous animals (including O-conotoxin and P-conotoxin superfamily members) with knottin scaffold. Knottins provide appealing scaffolds for protein engineering and drug design due to their small size, high structural stability, strong sequence tolerance and easy access to chemical synthesis. The sequence patterns and associated documentation files created by us should be useful in protein family classification and functional annotation. Even though patterns might be useful at the family level, they may not always be adequate at the superfamily level due to hypervariability of mature toxins. In order to overcome this problem, we have demonstrated the applicationos of multi-class support vector machines (MC-SVMs) for the successful in silico classification of the mature conotoxins into their superfamilies. TheI- and J-conotoxin-superfamily members were analyzed in greater detail. On the basis of in silico analysis, we have divided the 28 entries previously grouped as I-conotoxin superfamily in UniProtKB/Swiss-Prot (release 49.0) into I1 and I2 superfamilies inview of their having two different types of signal peptides and exhibiting distinct functions. A comparative study of the theoretically modeled structure of ViTx from Conus virgo, a typical member of I2-conotoxin superfamily, reveals the crucial role of C-terminal region of ViTx in blocking therapeutically important voltage-gated potassium channels. Putative complexes created by us of very recently characterized J-superfamily conotoxin p11-4a with Kv1.6 suggest that the peptide interacts with negatively charged extracellular loops and pore-mouth of the potassium channel and blocks the channel by covering the pore as a lid, akin to previously proposed blocking mechanism of kM-conotoxin RIIIK from Conus radiatus to Tsha1 potassium channel. This finding provides a pointer to experimental work to validate the observations made here. Based on differences in the number and distribution of the positively charged residues in other conopeptides from the J-superfamily, we hypothesize different selectivity profile against subtypes of the potassium channels for these conopeptides. Furthermore, the present thesis reports the application of order-statistic filters and hydrophobicity profiles for predicting the location of membrane-spanning helices. The Proposed method is in particular effective for the class of helical membrane proteins, namely the therapeutically important voltage-gated ion channels, which are natural targets of several conotoxins. Our suggested ab initio approach is comparatively better than other spatial filters, confirming to the efficacy of including the concept of order or ranking information for prediction of TM helicdes. Such approaches should be of value for improved prediction performance including in large-scale applications. In addition, anlaysis has been carried out of the role of context in the relationship between form and function for the true PDB hits of some nonCys-rich PROSITE patterns. We have found specific examples of true hits of some PROSITE patterns displaying structural plasticity by assuming significantly different local conformation, depending upon the context. The work was carried out as a part of the research interest in our group in studying structural and other features of protein sequence patterns. The Contributions of the candidate to venominormatics include, creation of protein sequence patterns and information highlighting the importance of the patterns as gleaned from the lteratures for family classification: profile HMM and MC-SVMs for conotoxin superfamily classification; in silico characterization of I1 and I2 conotoxin superfamilies; studies of interaction with Kv1 channels of typical members of I2 and 3 conotoxin superfamilies and development of improved methods for detecting membrane-spanning helices. Chapter I starts with a brief account of venominformatics; bioinformatics for venoms and toxins. Chapter 2 presents a regular expression based classification of Conus peptides. Chapter 3 revisits the 28 entries previously grouped as I-conotoxin superfamily in UniProt Swiss-Prot knowledgebase (release 49.0) having four disulfide bonds with Cys arrangement C-C-CC-CC-C-C and they inhibit or modify ion channels of nerve cells. Chapter 4 describes pseudo-amino acid composition and MC-SVMs approach for conotoxin superfamily classification. Chapter 5 describes in silico detection of binding mode with Kv1.6 channel of J-superfamily conotoxin p114a from bermivorouos cone snail, Conus planorbis. Chapter 6 presents a comparative sequence-structure-function analysis of naturally occurring Cys-rich peptides having the Knottin or inhibitor cystine knot(ICK) scaffold, from different plants and venomous animals based on information available in the knottin database(http://knottin.cbs.cnrs.fr/). Chapter 7 describes the application of order-statistic filters and hydrophobicity profiles for detecting membrane-spanning helices. Chapter 8 describes the role of context in the relationship between form and function for the true PDB hits of some non Cys-rich PROSITE patterns. Chapter 9 summaries the important findings of the present studies on naturally occurring bioactive Cys-rich peptides with emphasis on Conus peptides and their interactions with respective target such as voltage-gated ion channels.