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Готові списки джерел за темами / Structural bio-Informatics

Добірка наукової літератури з теми "Structural bio-Informatics"

Автор: Grafiati

Опубліковано: 8 червня 2024

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Статті в журналах з теми "Structural bio-Informatics":

1

Et. al., Ravi Kumar A,. "A Review on Design and Development of Performance Evaluation Model for Bio-Informatics Data Using Hadoop." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 1546–63. http://dx.doi.org/10.17762/turcomat.v12i2.1432.

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The paper reviews the usage of the platform Hadoop in applications for systemic bioinformatics. Hadoop offers another system for Structural Bioinformatics to break down broad fractions of the Protein Data Bank that is crucial to high-throughput investigations of (for example) protein-ligand docking, protein-ligand complex clustering, and structural alignment. In specific, we review different applications of high-throughput analyses and their scalability in the literature using Hadoop. In comparison to revising the algorithms, we find that these organisations typically use a realized executable called MapReduce. Scalability demonstrates variable behavior in correlation with other batch schedulers, particularly as immediate examinations are usually not accessible on a similar platform. Direct Hadoop examinations with batch schedulers are missing in the literature, but we note that there is some evidence that the scale of MPI executions is better than Hadoop. The dilemma of the interface and structure of an asset to use Hadoop is a significant obstacle to the utilization of the Hadoop biological framework. This will enhance additional time as Hadoop interfaces, such as enhancing Flash, increasing the use of cloud platforms, and normalized approaches, for example, are taken up by Workflow Languages.

2

Lakhrissi, Younes, Mohamed Rbaa, Burak Tuzun, Abdelhadi Hichar, El Hassane Anouar, Khadija Ounine, Faisal Almalki, Taibi Ben Hadda, Abdelkader Zarrouk, and Brahim Lakhrissi. "Synthesis, structural confirmation, antibacterial properties and bio-informatics computational analyses of new pyrrole based on 8-hydroxyquinoline." Journal of Molecular Structure 1259 (July 2022): 132683. http://dx.doi.org/10.1016/j.molstruc.2022.132683.

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3

Shimizu, Nobutaka, Shinya Saijyo, Hiromasa Ota, Yasuko Nagatani, Ai Kamijyo, Takeharu Mori, Takashi Kosuge, and Noriyuki Igarashi. "3P015 Bio-SAXS in the Platform for Drug Discovery, Informatics, and Structural Life Science (PDIS)(01A. Protein: Structure,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S214. http://dx.doi.org/10.2142/biophys.53.s214_3.

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4

George Priya Doss, C., C. Sudandiradoss, R. Rajasekaran, Rituraj Purohit, K. Ramanathan, and Rao Sethumadhavan. "Identification and structural comparison of deleterious mutations in nsSNPs of ABL1 gene in chronic myeloid leukemia: A bio-informatics study." Journal of Biomedical Informatics 41, no. 4 (August 2008): 607–12. http://dx.doi.org/10.1016/j.jbi.2007.12.004.

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5

Rahman, Monzilur, and Md Masud Parvege. "In silico structural analysis of Hantaan virus glycoprotein G2 and conserved epitope prediction for vaccine development." Journal of Applied Virology 3, no. 3 (September 19, 2014): 62. http://dx.doi.org/10.21092/jav.v3i3.38.

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<p>Hantaan virus (HNTV) is an etiological agent of potentially fatal hemorrhagic fever with renal syndrome (HFRS). The virus infects a large number of patients annually with a mortality rate more than 10%. However, no treatment option or vaccine is available against the virus. Between two envelope proteins, HNTV glycoprotein G2 has higher antigenicity making it a better target for vaccine development. However, 3-D structure of the protein is not available which is important for identifying epitopes that are essential for vaccine design. Therefore, this study was designed to predict a structural model of glycoprotein G2 and to predict peptide sequences for vaccine development containing conserved epitopes within the structure. Many of the physio-chemical and structural properties including secondary structure and di-sulfide linkage of the protein were predicted using a number of computational tools. <strong></strong>The 3D structure of the protein was modeled using I-TASSER online tool. The quality of the predicted models was evaluated with Ramachandran plot and Z-score. The structural and sequence information was used to predict B-cell and T-cell epitopes on glycoprotein G2. Using various bio-informatics and immuno-informatics tools, a total of 9 continuous B-cell and 22 T-cell epitopes were predicted having significant antigenicity. These antigenic epitopes were further analyzed for conservation and a total of 4 B-cells and 8 T-cell epitopes were found to be highly conserved in sequences from diverse origins. These epitopes revealed by the current study are recognized by immune system to protect host from HNTV infection can be potential targets for vaccine development.</p>

6

Kumar, Archana, T. B. Sridharn, and Kamini A. Rao. "Role of Seminal Plasma Proteins in Effective Zygote Formation- A Success Road to Pregnancy." Protein & Peptide Letters 26, no. 4 (March 28, 2019): 238–50. http://dx.doi.org/10.2174/0929866526666190208112152.

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Seminal plasma proteins contributed by secretions of accessory glands plays a copious role in fertilization. Their role is overlooked for decades and even now, as Artificial Reproduction Techniques (ART) excludes the plasma components in the procedures. Recent evidences suggest the importance of these proteins starting from imparting fertility status to men, fertilization and till successful implantation of the conceptus in the female uterus. Seminal plasma is rich in diverse proteins, but a major part of the seminal plasma is constituted by very lesser number of proteins. This makes isolation and further research on non abundant protein a tough task. With the advent of much advanced proteomic techniques and bio informatics tools, studying the protein component of seminal plasma has become easy and promising. This review is focused on the role of seminal plasma proteins on various walks of fertilization process and thus, the possible exploitation of seminal plasma proteins for understanding the etiology of male related infertility issues. In addition, a compilation of seminal plasma proteins and their functions has been done.

7

Gheraibia, Youcef, Abdelouahab Moussaoui, Youcef Djenouri, Sohag Kabir, Peng-Yeng Yin, and Smaine Mazouzi. "Penguin Search Optimisation Algorithm for Finding Optimal Spaced Seeds." International Journal of Software Science and Computational Intelligence 7, no. 2 (April 2015): 85–99. http://dx.doi.org/10.4018/ijssci.2015040105.

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This paper develops PeSeeD, a new metaheuristic algorithm for finding optimal spaced seed. Sequences matching is a hot topic in bio-informatics, which is used in many applications such as understanding the functional, structural, or evolutionary relationships between the sequences. The most relevant sequences matching methods are based on seeds designed to match two biological sequences. The first approach which introduced seeds was facilitated via Blastn tool, the approach builds seeds of 11 length size. However, it is clear that not all local alignments have to include an identical fragment of length 11. The spaced seeds approach is one of the methods which does not require a consecutive matching position. Dynamic programming is used to solve this kind of problem and it takes quadratic time. Several approaches have then been proposed to improve the sensitivity of searching in reasonable runtime. To reduce the complexity of such approaches, other heuristics based approaches can also be reviewed. The aim is to find spaced seeds subset which improves sensitivity without increasing the computation time. In this paper, the optimal subset spaced seeds are explored using the bio-inspired approach, penguins search optimisation algorithm (‘'PeSOA'' for short). The authors further propose an efficient heuristic for computing the overlap complexity between seeds. To evaluate the efficiency of the proposed approach, they compared the obtained results with the results of several seeds based software tools. The obtained results are very promising in terms of sensitivity and computation time for the overlap complexity.

8

Javed, Ambreen, Gulshan Ara Trali, Hassan Burair Abbas, and Alia Sadiq. "IN SILICO CHARACTERIZATION OF HUMAN INTERFERON ALPHA/BETA RECEPTOR 2 (ISOFORM A, B AND C) PROTEIN." PAFMJ 71, no. 6 (December 31, 2021): 2091–94. http://dx.doi.org/10.51253/pafmj.v71i6.6571.

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Objective: To predict the tertiary structure of human interferon alpha/beta receptor 2 protein. Study Design: Structure prediction by using bio informatics tools. Place and Duration of Study: Department of Biochemistry, Swat Medical College (STMC), Saidu Shareef, Swat, Pakistan, from Aug 2019 to Dec 2019. Methodology: All protein sequences of human interferon alpha/beta receptor 2 (isoforma, b and c) (IFNAR-2) were retrieved through the BLAST search (The Basic Local Alignment Search Tool) from available databases ‘NCBI’ (National Centre for Biotechnology Information) and ‘Uni Prot KB’ (The Universal Protein Resource). Sequence alignment was conducted by using Clustal Omega, to get the consensus sequence for IFNAR-2 protein. Consensus protein sequence of human IFNAR-2 was used for the prediction of the three-dimensional structure by employing Swiss-Model Server. Moreover, subcellular localization analysis was also performed by using CELLO2GO program. Results: Structural model of human IFNAR-2 protein was predicted and evaluated by Ramachandran dimension. Cellular localization of tertiary topological domains of the predicted models were revealed probability of localization of IFNAR-2 protein (isoform a, b & c) is highest in the plasma membrane due to the presence of the transmembrane alpha helical regions. Conclusion: This study predicted the tertiary structural dimensions of human IFNAR-2 protein, including the specific topological domains that contribute towards the subcellular compartmentalization and functional characteristics.

9

Lakhrissi, Younes, Mohamed Rbaa, Burak Tuzun, Abdelhadi Hichar, El Hassane Anouar, Khadija Ounine, Faisal Almalki, Taibi Ben Hadda, Abdelkader Zarrouk, and Brahim Lakhrissi. "Corrigendum to ‘Synthesis, Structural confirmation, Antibacterial Properties and Bio-Informatics Computational Analyses of New Pyrrole Based on 8-Hydroxyquinoline’ Journal of Molecular Structure 1259 (2022) 132683." Journal of Molecular Structure 1280 (May 2023): 134988. http://dx.doi.org/10.1016/j.molstruc.2023.134988.

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10

Khuntia, Bharat Krushna, Vandna Sharma, Sahar Qazi, Soumi Das, Shruti Sharma, Khalid Raza, and Gautam Sharma. "Ayurvedic Medicinal Plants Against COVID-19: An In Silico Analysis." Natural Product Communications 16, no. 11 (November 2021): 1934578X2110567. http://dx.doi.org/10.1177/1934578x211056753.

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Even after one and a half years since the outbreak of COVID-19, its complete and effective control is still far from being achieved despite vaccination drives, symptomatic management with available drugs, and wider lockdowns. This has inspired researchers to screen potential phytochemicals from medicinal plants against SARS-CoV-2, adopting a bio-informatics approach. The current study aimed to assess anti-viral activity of the phytochemicals derived from Ayurvedic medicinal plants against SARS-CoV-2 drug targets [3-chymotrypsin-like protease (3CLpro) and RNA dependent RNA polymerase (RdRp)] using validated in silico methods.3D Structures of 196 phytochemicals from three Ayurvedic plants were retrieved from PubChem and KNApSAcK databases and screened for Absorption Distribution Metabolism Excretion and Toxicity(ADMET) to predict drug-likeness. The phytochemicals were subjected to molecular docking and only three showed promise: Acetovanillonewith a binding affinity of −4.7Kcal/mol with RdRp and −4.1 Kcal/mol with 3CL pro; myrtenol with equivalent values of −4.3 Kcal/mol with RdRP and −3.2 Kcal/mol with 3CLpro; and nimbochalcin with equivalent values of −5.0Kcal/mol with RdRp and −4.9 Kcal/mol with 3CLpro. Molecular dynamics simulation (50ns) analysis was made of 3CLpro and RdRp using Autodock Vina 1.1.2 software and VMD software. After ADMET analysis, 78 phytochemicals were found suitable for molecular docking. Three, namely acetovanillone, myrtenol and nimbochalcin from Picrorhiza kurroa, Azadirachta indica and Cyperus rotundus,respectively,exhibited good binding affinity with 3CLproand RdRp of SARS-CoV-2. Interaction analysis, molecular dynamics simulations and MM-PBSA calculations were executed for two complexes, acetovanillone_RdRp and myrtenol_3CL pro.Acetovanillone_RdRpcomplex did not display any structural change after MD simulation as compared to myrtenol_3CL pro. The overall stability of acetovanillone_6NUR was 154.7 kJ/mol, and for myrtenol_1UJ1 90.5 kJ/mol. In silico analysis revealed that acetovanillone ( Picrorhiza kurroa) and myrtenol ( Cyperus rotundus) possess anti SARS-CoV-2 activity. Further studies are needed to validate their efficacy in biological models.

Більше джерел

Дисертації з теми "Structural bio-Informatics":

1

Moniot, Antoine. "Modélisation 3D de complexes ARN-protéine par assemblage combinatoire de fragments structuraux." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0339.

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La caractérisation des complexes ARN-protéine à l'échelle atomique nous permet de mieux comprendre les fonctions de ces complexes, et de définir des cibles thérapeutiques pour réguler les phénomènes biologiques auxquels ils participent. L'objet de cette thèse est de développer des outils permettant de prédire la structure d'un complexe protéine-ARN lorsque l'on connaît une structure 3D de la protéine ainsi que la structure secondaire de la partie d'ARN en interaction. Nous nous concentrons sur le cas où l'ARN est principalement sous forme simple brin (nucléotides non appariés), posant la difficulté de sa flexibilité. Une méthode d'amarrage développée dans l'équipe CAPSID repose sur l'utilisation de fragments structuraux d'ARN simple brin. Le travail de cette thèse s'est appuyé sur cette méthode pour réaliser l'amarrage de structures secondaires de l'ARN. Nous avons d'abord évalué l'apport d'une contrainte de fermeture de boucle pour l'amarrage de la boucle simple brin d'une structure en épingle, puis abordé l'amarrage des éléments double brin de ces structures, ouvrant la voie à l'assemblage du complexe entier. Cette méthode d'amarrage est dépendante de l'utilisation de bibliothèques de fragments structuraux. Ces bibliothèques sont composées de prototypes qui représentent le paysage conformationnel observé expérimentalement dans les structures d'ARN liés à des protéines. Une large partie du travail de thèse a consisté en la création et l'optimisation de telles bibliothèques de fragments. Nous avons créé l'outil ProtNAff qui permet d'extraire de la PDB des sous-ensembles de structures et de créer des bibliothèques de fragments d'acides nucléiques, suivant des combinaisons complexes de critères. Il a été conçu de façon à dépasser nos besoins, afin d'être adopté par la communauté pour le traitement de problèmes variés. Nous avons développé une nouvelle approche pour l'inférence de prototypes représentatifs d'un ensemble de conformations. L'ensemble de prototypes doit satisfaire deux contraintes contradictoires: être représentatif (au sens de la métrique) et de cardinalité aussi petite que possible. Le problème se réduit donc à celui de l'inférence d'un epsilon-réseau de cardinalité minimale. Nous le traitons dans toute sa généralité en discutant des ensembles sur lesquels sont définies les données. Notre méthode se base sur la classification ascendante hiérarchique avec comme linkage le rayon des plus petites boules englobant les points de chaque sous-ensemble. Appliquée à nos bibliothèques, cette approche a permis de réduire d'un facteur 4 leur taille, et d'autant nos temps de calcul d'amarrage, tout en améliorant leur fiabilité. Enfin, pour pallier le problème posé par les superpositions de structures deux à deux, nous avons utilisé une représentation des fragments en coordonnées internes permettant de réduire encore les temps de calcul de création des bibliothèques
The characterization of RNA-protein complexes at the atomic scale allows us to better understand the biological functions of these complexes, and to define therapeutic targets to regulate the biological phenomena in which they participate. The aim of this thesis is to develop tools to predict the structure of a protein-RNA complex when a 3D structure of the protein is known as well as the secondary structure of the interacting RNA part. We focus on the case where RNA is mainly in single-stranded form (unpaired nucleotides), raising the difficulty of its flexibility.A docking method developed in the CAPSID team is based on the use of structural fragments of single-stranded RNA. The work of this thesis builds on this method to perform docking of RNA secondary structures. We first evaluated the contribution of a loop closure constraint for docking the single-stranded loop of a hairpin structure, and then addressed the docking of the double-stranded elements of these structures, paving the way for the assembly of the entire complex.This fragment-based docking method is dependent on the use of structural fragment libraries. These libraries are composed of prototypes that represent the conformational landscape experimentally observed in protein-bound RNA structures. A large part of the thesis work consisted in the creation and optimization of such fragment libraries.We created the ProtNAff tool that allows to extract subsets of structures from the PDB and to create libraries of nucleic acid fragments, following complex combinations of criteria. It has been designed to exceed our needs, so that it can be adopted by the community for the treatment of various problems.We have developed a new approach for inferring prototypes of a set of conformations. The set of prototypes must satisfy two contradictory constraints: to be representative (in the sense of the metric) and of cardinality as small as possible. The problem thus reduces to that of inferring an epsilon-network of minimal cardinality. We treat it in all its generality by discussing the spaces on which the data are defined. Our method is based on hierarchical agglomerative classification with as linkage the radius of the minimum balls enclosing the points of each subset. Applied to our libraries, this approach reduced their size by a factor of 4, and our docking computation time by the same amount, while improving their reliability.Finally, to overcome the problem posed by the pairwise superimposition of structures, we used a representation of the fragments in internal coordinates, allowing to reduce further the computation time for the creation of libraries

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Taveneau, Cyntia. "Modélisation, purification et caractérisation des modules et domaines de la PI4KA humaine." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA114827/document.

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La phosphatidylinositol-4-kinase de type IIIα est une kinase de lipide eukaryote ubiquitaire qui synthétise le phosphatidylinositol-4-phosphate PtdIns(4)P de la membrane plasmique. Ce phosphoinositide est d’autant plus important qu’il tient un rôle majeur dans différentes voies de signalisation cellulaire, le traffic vésiculaire ainsi que dans l’identité des organelles. De plus, la PIK4A humaine est un facteur essentiel pour la réplication du virus de l’hépatite C (VHC). En effet, le recrutement du complexe de réplication du VHC par la protéine virale NS5A à la membrane du reticulum endoplasmique permet la formation d’un réseau membranaire à l’origine de la structuration des complexes de replication viraux.La PI4KA est une kinase imposante (2102 résidus, 240 kDa pour la PI4KA humaine) qui possède un domaine kinase C-terminal d’environ 400 résidus précédé d’un domaine formé de répétitions Armadillo pour lequel aucune fonction n’a été determinée. Le rôle ainsi que le repliement des 1500 résidus N-terminaux de PI4KA ne sont pas connus à ce jour.Afin d’en savoir plus sur la structure tri-dimensionnelle de la PI4KA humaine, nous avons utilisé des outils bio-informatiques afin de délimiter et de modéliser les modules et domaines la composant. Nous avons pu ainsi les exprimer et les produire en bactérie et en cellules d’insecte afin de vérifier nos hypothèses. Nous avons pu conclure que PI4KA est composée de deux modules. Le module N-terminal (1100 résidus), est composé de deux domaines dont un solénoïde α. Les résultats obtenus par diffusion des rayons X aux petits angles (SAXS) nous permettent de définir leur agencement potentiel. Le second module (1000 résidus), le module C-terminal, est l’enzyme-core. Son analyse nous a permis d’identifier une similitude remarquable avec les sérine/thréonine kinases PIKKs, comme mTor, apparentées aux phosphatidylinositol-3-kinases. Nous avons défini au début du module C-terminal de PI4KA trois domaines putatifs que nous avons nommés DI, DII et DIII. Nos collaborateurs ont montré qu'ils sont essentiels à l’activité kinase de la protéine ainsi qu’à la replication du VHC. Le domaine DI a été caractérisé et a permis la validation d’une nouvelle paramétrisation de la molécule de N, N-dimethyl-dodecylamine oxide (LDAO) pour des simulations de dynamique moléculaire. Enfin, la PI4KA humaine dans son entier a été exprimée en cellules d’insecte puis purifiée, et un premier test d’interaction avec les membranes a été initié
The eukaryotic lipid kinase phosphatidylinositol 4-kinase III alpha is a ubiquitous enzyme that synthesizes the plasma membrane pool of phosphatidylinositol 4-phosphate. This important phosphoinositide has key roles in different signalization pathways, vesicular traffic and cellular compartment identity. Moreover, PI4KA is an essential factor for hepatitis C virus (HCV) replication. Indeed, PI4KA's interaction with the non-structural HCV protein NS5A at the endoplasmic reticulum membrane leads to formation of a “membranous web” giving to the membrane the signature necessary to the formation of viral replication machineryPI4KA is a large protein (2102 residues, 240 kDa for human PI4KA) with the kinase domain making up the ca 400 C-terminal residues preceded by an Armadillo domain for which no function is known. There is essentially no structural information about the 1500 N-terminal residues and no clue as to the function of most of this region of PI4KA.We use computational methods in order to delineate fragments of human PI4KA amenable to soluble production in Escherichia coli and insect cells. We clone and express these fragments and evaluate the soluble fraction of each construction. Our results further suggest that PI4KA can be described as a two-module protein. The N-terminal module (1100 residues), is composed of two domains which one is an alpha solenoid. Their potential arrangement was defined by small angle X-ray scattering (SAXS).The second module (1000 residues), the C-terminal module, is the core enzyme. Its analysis leads us to identify similarities with the serine/threonine kinases PIKKs, as mTor, homologous to phosphatidylinositol-3-kinases. Three putative domains were delineate at the beginning of this C-terminal module. We name the DI, DII and DIII. Our collaborators have shown their necessity to the kinase activity of PI4KA and the HCV replication. DI domain was characterized and allowed the validation of a new parametrization of the N, N-dimethyl-dodecylamine oxide molecule (LDAO) for simulation of molecular dynamics. Finally, the full-length human PI4KA was expressed in insect cells, purified and a first interaction experiment with membranes have been initiated

Частини книг з теми "Structural bio-Informatics":

1

Zhou, Linfei, Elisabeth Georgii, Claudia Plant, and Christian Böhm. "Covariate-Related Structure Extraction from Paired Data." In Information Technology in Bio- and Medical Informatics, 151–62. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43949-5_11.

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2

Lu, Jing, Alan Hales, and David Rew. "Modelling of Cancer Patient Records: A Structured Approach to Data Mining and Visual Analytics." In Information Technology in Bio- and Medical Informatics, 30–51. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64265-9_4.

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3

Rudolfova, Ivana, Jaroslav Zendulka, and Matej Lexa. "Clustering of Protein Substructures for Discovery of a Novel Class of Sequence-Structure Fragments." In Information Technology in Bio- and Medical Informatics, ITBAM 2010, 94–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15020-3_9.

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4

S., Karthigai Selvi. "Structural and Functional Data Processing in Bio-Computing and Deep Learning." In Research Anthology on Bioinformatics, Genomics, and Computational Biology, 1453–66. IGI Global, 2023. http://dx.doi.org/10.4018/979-8-3693-3026-5.ch066.

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The goal of new biocomputing research is to comprehend bio molecules' structures and functions via the lens of biofuturistic technologies. The amount of data generated every day is tremendous, and data bases are growing exponentially. A majority of computational researchers have been using machine learning for the analysis of bio-informatics data sets. This chapter explores the relationship between deep learning algorithms and the fundamental biological concepts of protein structure, phenotypes and genotype, proteins and protein levels, and the similarities and differences between popular deep learning models. This chapter offers a useful outlook for further research into its theory, algorithms, and applications in computational biology and bioinformatics. Understanding the structural aspects of cellular contact networks helps to comprehend the interdependencies, causal chains, and fundamental functional capabilities that exist across the entire network.

5

S., Karthigai Selvi. "Structural and Functional Data Processing in Bio-Computing and Deep Learning." In Structural and Functional Aspects of Biocomputing Systems for Data Processing, 198–215. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6523-3.ch010.

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The goal of new biocomputing research is to comprehend bio molecules' structures and functions via the lens of biofuturistic technologies. The amount of data generated every day is tremendous, and data bases are growing exponentially. A majority of computational researchers have been using machine learning for the analysis of bio-informatics data sets. This chapter explores the relationship between deep learning algorithms and the fundamental biological concepts of protein structure, phenotypes and genotype, proteins and protein levels, and the similarities and differences between popular deep learning models. This chapter offers a useful outlook for further research into its theory, algorithms, and applications in computational biology and bioinformatics. Understanding the structural aspects of cellular contact networks helps to comprehend the interdependencies, causal chains, and fundamental functional capabilities that exist across the entire network.

6

Raghupathi, Wullianallur, and Sridhar Nerur. "The Intellectual Structure of Health and Medical Informatics." In Advancing Technologies and Intelligence in Healthcare and Clinical Environments Breakthroughs, 1–16. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1755-1.ch001.

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This paper presents the results of an author co-citation analysis of the health and medical informatics discipline. It updates a smaller study that focused on health information systems. Drawing on such sub-fields as bio informatics, clinical decision support systems, computational genomics, e-health, health informatics, and others, this body of knowledge defines the core internal structure of the discipline and delineates its sub-fields. An author co-citation analysis was performed for a nine-year period using the members of editorial boards of several medical informatics-related journals as an initial author sample (N = 272). Several multivariate analyses, including cluster analysis, factor analysis and multidimensional scaling, were performed. The authors results confirm that several established sub-fields still stand but a number of new sub-fields are emerging. Future research can build on this work and examine other journals and additional authors to gain insights into the collaborative and interdisciplinary nature of the health and medical informatics discipline.

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YAMATO, ICHIRO. "FROM STRUCTURE AND FUNCTION OF PROTEINS TOWARDIN SILICOBIOLOGY." In Quantum Bio-Informatics V, 473–85. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814460026_0040.

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HARA, TOSHIHIDE, KEIKO SATO, and MASANORI OHYA. "PROTEIN SEQUENCE ALIGNMENT TAKING THE STRUCTURE OF PEPTIDE BOND." In Quantum Bio-Informatics V, 181–85. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814460026_0015.

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ORYU, SHINSHO. "LONG-RANGE PROPERTY IN TIME-DEPENDENT INTERACTION WITH THREE-BODY STRUCTURE AND NEW ASPECT." In Quantum Bio-Informatics V, 253–69. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814460026_0022.

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SUZUKI, TOMONORI, and SATORU MIYAZAKI. "THE PREDICTION OF BOTULINUM TOXIN STRUCTURE BASED ON IN SILICO AND IN VITRO ANALYSIS." In Quantum Bio-Informatics IV, 461–67. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814343763_0036.

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Тези доповідей конференцій з теми "Structural bio-Informatics":

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SAHA, ACHINTYA, and TABASSUM HOSSAIN. "Molecular modeling studies for exploring structural requirement of acetylcholinesterase inhibitors." In Fourth International Conference on Advances in Bio-Informatics and Environmental Engineering - ICABEE 2016. Institute of Research Engineers and Doctors, 2016. http://dx.doi.org/10.15224/978-1-63248-100-9-17.

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ZUNIGA, ALEJANDRO, ARYANE TOFANELLO, CARLOS E, ERICA G, FERNANDO C, ISELI L, and JULIANA C. "Self assembled complexes of multibranched gold nanoparticles with porphyrins used in photodynamic therapy Spectral and structural characterization." In Second International Conference on Advances in Bio-Informatics and Environmental Engineering - ICABEE 2015. Institute of Research Engineers and Doctors, 2015. http://dx.doi.org/10.15224/978-1-63248-043-9-102.

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Mukherjee, Sudipta, Somnath Chakraborty, Deven Diwakar, Apurba Laha, Udayan Ganguly, and Swaroop Ganguly. "Investigation of Structural Parameter Variation on Extended Gate TFET for Bio-Sensor Applications." In 2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI). IEEE, 2020. http://dx.doi.org/10.23919/eecsi50503.2020.9251884.

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SUZUKI, TOMONORI, and SATORU MIYAZAKI. "IN SILICO ANALYSIS FOR THE STUDY OF BOTULINUM TOXIN STRUCTURE." In From Quantum Information to Bio-Informatics. WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814304061_0039.

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CAKAN, BANU, SAIT BASARAN, SEVIM AKYUZ, and TANIL AKYUZ. "Protein Structure Predictions of historical silk textiles by ATR FTIR spectroscopy." In Third International Conference on Advances in Bio-Informatics, Bio-Technology and Environmental Engineering- ABBE 2015. Institute of Research Engineers and Doctors, 2015. http://dx.doi.org/10.15224/978-1-63248-060-6-09.

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Pisal, Amit, and Rabinder Henry. "Thermo-Optic switch: Device structure and design." In 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB). IEEE, 2016. http://dx.doi.org/10.1109/aeeicb.2016.7538293.

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Mishra, Loveneet, Sampath Kumar V, and Sangeeta Mangesh. "Design and implementation of low power SRAM structure using nanometer scale." In 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB). IEEE, 2016. http://dx.doi.org/10.1109/aeeicb.2016.7538407.

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Ramesh, M., V. Rajya Lakshmi, and P. Mallikarjuna Rao. "Investigation on UWB kite shape textile antenna with Defective Ground Structure." In 2017 Third International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB). IEEE, 2017. http://dx.doi.org/10.1109/aeeicb.2017.7972374.

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Arabi, Punal M., Prathibha T.P, Vamsha Deepa N, and AbhikRaj Subedi. "Identifying honeycombing structure in HRCT lung images by high intensity pixel pattern." In 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB). IEEE, 2016. http://dx.doi.org/10.1109/aeeicb.2016.7538336.

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Rameswarudu, E. Sarva, and P. V. Sridevi. "Bandwidth enhancement defected ground structure microstrip patch antenna for K and Ka band applications." In 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB). IEEE, 2016. http://dx.doi.org/10.1109/aeeicb.2016.7538318.

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