Literatura científica selecionada sobre o tema "Chemo-Informatics"
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Artigos de revistas sobre o assunto "Chemo-Informatics"
Vandewiele, Nick M., Kevin M. Van Geem, Marie-Françoise Reyniers e Guy B. Marin. "Genesys: Kinetic model construction using chemo-informatics". Chemical Engineering Journal 207-208 (outubro de 2012): 526–38. http://dx.doi.org/10.1016/j.cej.2012.07.014.
Texto completo da fonteHawash, Mohammed, Nidal Jaradat, Murad Abualhasan, Johnny Amer, Serkan Levent, Shahd Issa, Sameeha Ibrahim, Aseel Ayaseh, Tahrir Shtayeh e Ahmed Mousa. "Synthesis, chemo-informatics, and anticancer evaluation of fluorophenyl-isoxazole derivatives". Open Chemistry 19, n.º 1 (1 de janeiro de 2021): 855–63. http://dx.doi.org/10.1515/chem-2021-0078.
Texto completo da fonteKassab, Mohammed. "DEVELOPMENT OF NOVEL ANTIMICROBIAL TETRACYCLINE ANALOG B (IODOCYCLINE) BY CHEMO-INFORMATICS." Ain Shams Medical Journal 74, n.º 1 (1 de março de 2023): 303–15. http://dx.doi.org/10.21608/asmj.2022.159722.1042.
Texto completo da fonteKassab, Mohammed. "DEVELOPMENT OF NOVEL ANTIMICROBIAL TETRACYCLINE ANALOG B (IODOCYCLINE) BY CHEMO-INFORMATICS." Ain Shams Medical Journal 73, n.º 4 (1 de dezembro de 2022): 969–81. http://dx.doi.org/10.21608/asmj.2022.285476.
Texto completo da fonteBajorath, Jürgen. "Rational drug discovery revisited: interfacing experimental programs with bio- and chemo-informatics". Drug Discovery Today 6, n.º 19 (outubro de 2001): 989–95. http://dx.doi.org/10.1016/s1359-6446(01)01961-4.
Texto completo da fonteStahura, Florence L., e Jürgen Bajorath. "Bio- and chemo-informatics beyond data management: crucial challenges and future opportunities". Drug Discovery Today 7, n.º 11 (maio de 2002): S41—S47. http://dx.doi.org/10.1016/s1359-6446(02)02271-7.
Texto completo da fonteTsochatzis, Emmanouil, Joao Alberto Lopes, Fabiano Reniero, Margaret Holland, Jenny Åberg e Claude Guillou. "Identification of 1-Butyl-Lysergic Acid Diethylamide (1B-LSD) in Seized Blotter Paper Using an Integrated Workflow of Analytical Techniques and Chemo-Informatics". Molecules 25, n.º 3 (7 de fevereiro de 2020): 712. http://dx.doi.org/10.3390/molecules25030712.
Texto completo da fonteScherbinina, Sofya I., e Philip V. Toukach. "Three-Dimensional Structures of Carbohydrates and Where to Find Them". International Journal of Molecular Sciences 21, n.º 20 (18 de outubro de 2020): 7702. http://dx.doi.org/10.3390/ijms21207702.
Texto completo da fonteLafata, Jennifer Elston, Stephen Harris, Megan Fasold, Audrey Holdren e Hanna Kelly Sanoff. "Building a population management informatics infrastructure for oncology care." Journal of Clinical Oncology 37, n.º 27_suppl (20 de setembro de 2019): 315. http://dx.doi.org/10.1200/jco.2019.37.27_suppl.315.
Texto completo da fontePedretti, Alessandro, Luigi Villa e Giulio Vistoli. "VEGA – An open platform to develop chemo-bio-informatics applications, using plug-in architecture and script programming". Journal of Computer-Aided Molecular Design 18, n.º 3 (março de 2004): 167–73. http://dx.doi.org/10.1023/b:jcam.0000035186.90683.f2.
Texto completo da fonteTeses / dissertações sobre o assunto "Chemo-Informatics"
Sasi, Abd-Alkarim Nour-Addin. "Cardiovascular effects, molecular docking and chemo informatics analysis of compounds isolated from leonotis leonurus". Thesis, University of the Western Cape, 2015. http://hdl.handle.net/11394/5342.
Texto completo da fonteLeonotis leonurus (L. Leonurus) has relatively abundant diterpenes and has been used as a traditional herbal medicine for treating several ailments including influenza, muscular cramps, skin related diseases, menstrual, antilipidemic, hyperglycaemia and hypertension. In this study, diterpenoid compounds such as; Dubiin, SaponifiedDubiin, Hispanol, Marrubiin and DC9 were isolated from L. Leonurus plant. The cardiovascular effects of these isolated compounds were investigated in order to determine the response of anaesthetised normotensive Wistar rats (in-vivo) to the compounds. Also, the druglikeness of the isolated diterpenoid compounds and their binding interaction with β1 adrenoceptor (PDB: 2Y04), angiotensin II receptor (Ang II) (PDB: 3R8A), Angiotensin converting enzyme (ACE) (PDB: 4XX3), and renin receptor (PDB: 2X8Z) by using molecular docking methods and Chemoinformatics analysis was performed (in-silico). Important molecular descriptors and molecular docking were used in our Chemoinformatics (in-silico) analysis to study the druglikeness and the binding affinity for of each molecule (Dubiin, SaponifiedDubiin, Hispanol, Marrubiin and DC9). The molecular descriptors and the binding energy were calculated by using the molecular operating environment software (MOE 2013). The lowest energy and highest cluster conformations of the molecules were further analysed. All the five (5) diterpenoids were predicted to have good oral bioavailability after oral administration and passed the BloodBrain Barrier (BBB) rules. Also, the compounds were predicted to have high probability of being good Druglike candidates, except for DC9, which is predicted to have lower possibilities of being Druglike candidate than the other diterpenoids. Furthermore, these compounds (Dubiin, SaponifiedDubiin, Hispanol, Marrubiin and DC9) were shown to interact with β1 adrenoceptors in-silico, an interaction that was confirmed in-vivo by increases in Blood pressure (SP, DP and MAP) and Heart rate (HR). In anaesthetized normotensive male Wistar rats (in-vivo), Dubiin (0.5 40mg/kg; IV), SaponifiedDubiin (0.5 60mg/kg; IV) Hispanol (0.5 40mg/kg; IV), DC9 (0.5 40mg/kg; IV) and Marrubiin (0.5 40mg/kg; IV) produced dose dependent increase in Systolic pressure (SP), Diastolic pressure (DP), and Mean arterial pressure (MAP) at all doses. Also, the compounds produced dose dependent increase in Heart rate (HR). From the in-vivo and in-silico studies it can be concluded that all the five (5) isolated diterpenoid compounds showed cardiovascular effects on Blood pressure (BP) and Heart rate (HR) by acting as β1 adrenoceptor agonists. Also, these diterpenoids compounds could be responsible for the cardiovascular effect observed in the methanol extracts from previous studies. These cardioactive compounds are prototype or ''lead compounds'' for designing and developing new nontoxic and effective drugs for cardiovascular disease (CVD) treatment.
Nouleho, ilemo Stefi. "Algorithmique de graphes pour la similarité structurelle de molécules et de réactions". Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG028.
Texto completo da fonteA synthesis pathway is, for a given molecule, a sequence of reactions making possible to obtain it from purchasable molecules or easily synthesizable. In chemoinformatics, predicting or assisting the conception of synthesis pathways for new molecules is a challenge. It consists in analyzing the very large databases of existing molecular reactions to build new synthesis pathways from existing plans of similar molecules. In this context, the similarity between molecules relies on their topology.We introduce a structural representation of molecules called the graph of cycles. This representation is based on the cycles in the molecular graph and their interconnections.This representation is canonical and allows us to define a similarity measure between structures of molecules and is computable in a reasonable amount of time. Our studies show that it is more adapted for works on synthesis pathways than the other existing similarity measures.Based on the graph of cycles, we proposed a classification of reactions according to the effects on the structure of molecules. This is the first step for the prediction of synthesis pathways
Bougueroua, Sana. "Caractérisation de structures explorées dans les simulations de dynamique moléculaire". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLV099/document.
Texto completo da fonteThis PhD is part of transdisciplinary works, combining graph theory and computational chemistry.In molecular dynamics simulations, a molecular system can adopt different conformations over time. Along a trajectory, one conformation or more can thus be explored. This depends on the simulation time and energy within the system. To get a good exploration of the molecular conformations, one must generate and analyse several trajectories (this can amount to thousands of trajectories). Our objective is to propose an automatic method that provides rapid and efficient analysis of the conformational dynamics explored over these trajectories. The trajectories of interest here are in cartesian coordinates of the atoms that constitute the molecular system, recorded at regular time intervals (time-steps). Each interval containing a set of positions is called a snapshot. At each snapshot, our developed algorithm uses geometric rules (distances, angles, etc.) to compute bonds (covalent bonds, hydrogen bonds and any other kind of intermolecular criterium) formed between atoms in order to get the mixed graph modelling one given conformation. Within our current definitions, a conformational change is characterized by either a change in the hydrogen bonds or in the covalent bonds. One choice or the other depends on the underlying physics and chemistry of interest. The proposed algorithm provides all conformations explored along one or several trajectories, the period of time for the existence of each one of these conformations, and also provides the graph of transitions that shows all conformational changes that have been observed during the trajectories. A user-friendly interface has been developed, that can de distributed freely.Our proposed algorithm for analysing the trajectories of molecular dynamics simulations has been tested on three kinds of gas phase molecular systems (peptides, ionic clusters). This model can be easily adapted and applied to any other molecular systems as well as to condensed matter systems, with little effort. Although the theoretical complexity of the algorithm is exponential (isomorphism tests), results have shown that the algorithm is rapid.We have also worked on computationally low cost graph methods that can be applied in order to pre-characterize specific conformations/points on a potential energy surface (it describes the energy of a system in terms of positions of the atoms). These points are the minima on the surface, representing the most stable conformations of a molecular system, and the maxima on that surface, representing transition states between two conformers. Our developed methods and algorithms aim at getting these specific points, without the prerequisite knowledge/calculation of the potential energy surface by quantum chemistry methods (or even by classical representations). By avoiding an explicit calculation of the potential energy surface by quantum chemistry methods, one saves computational time and effort. We have proposed an alternative method using ad doc measures based on properties of the graphs (already used in the first part of the PhD), without any knowledge of energy and/or molecular calculations. These measures allow getting the possible conformations with a realistic energy classification, as well as transition states, at very low computational cost. The algorithm has been tested on gas phase peptides
Capítulos de livros sobre o assunto "Chemo-Informatics"
Sandjakoska, Ljubinka, Ana Madevska Bogdanova e Ljupcho Pejov. "Novel Methodology for Improving the Generalization Capability of Chemo-Informatics Deep Learning Models". In Communications in Computer and Information Science, 161–74. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-22792-9_13.
Texto completo da fonteNguyen, Quynh T. N., Phuc T. Phan, Shwu-Jiuan Lin, Min-Huei Hsu, Yu-Chuan (Jack) Li, Jason C. Hsu e Phung-Anh Nguyen. "Machine-Learning Based Risk Assessment for Cancer Therapy-Related Cardiac Adverse Events Among Breast Cancer Patients". In Studies in Health Technology and Informatics. IOS Press, 2024. http://dx.doi.org/10.3233/shti231116.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Chemo-Informatics"
Rasulev, Bakhtiyor. "APPLICATION OF COMBINED DATA-DRIVEN COMPUTATIONAL CHEMISTRY AND CHEMINFORMATICS APPROACHES TO PREDICT PROPERTIES OF MATERIALS". In 1st INTERNATIONAL Conference on Chemo and BioInformatics. Institute for Information Technologies, University of Kragujevac,, 2021. http://dx.doi.org/10.46793/iccbi21.002r.
Texto completo da fonte