作者: 發(fā)生 時(shí)間: 2025-3-21 22:48
https://doi.org/10.1057/9780230375130earch and potential applications of QSAR modeling tools toward the rational design of more efficient antibacterial agents. Particular emphasis is given to the setup of multitasking models along with ANNs aimed at jointly predicting different antibacterial activities and safety profiles of drugs/chem作者: FIG 時(shí)間: 2025-3-22 03:18
On Barbie, the Boob, and Loaeza,tool that is powered by the widely used machine learning package Weka. The software provides a user-friendly graphical interface along with an automated parameter search capability. It employs two robust and popular machine learning methods: artificial neural networks and support vector machines. Th作者: 訓(xùn)誡 時(shí)間: 2025-3-22 07:10 作者: vocation 時(shí)間: 2025-3-22 10:45
Damian Griffin,Shanmugam Karthikeyanes a compact holistic representation of the data and is thus an efficient way to encode a large set of views. Second, as we do not store the training views, we are not limited in the number of training views we use and the agent does not need to decide which views to learn.作者: 字的誤用 時(shí)間: 2025-3-22 13:29 作者: coagulate 時(shí)間: 2025-3-22 17:40 作者: Forehead-Lift 時(shí)間: 2025-3-22 22:26 作者: 健談的人 時(shí)間: 2025-3-23 01:33
1064-3745 nd practical, .Artificial Neural Networks: Second Edition. aids scientists in continuing to study Artificial Neural Networks (ANNs)..978-1-4939-4893-2978-1-4939-2239-0Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: 不感興趣 時(shí)間: 2025-3-23 07:25
Introduction to the Analysis of the Intracellular Sorting Information in Protein Sequences: From Mosis and localization/trafficking prediction. We provide the rationale for and a discussion of a simple basic protocol for protein sequence dissection looking for sorting signals, from simple sequence inspection techniques to more sophisticated artificial neural networks analysis of sorting signal re作者: 不出名 時(shí)間: 2025-3-23 13:22
A General ANN-Based Multitasking Model for the Discovery of Potent and Safer Antibacterial Agents,earch and potential applications of QSAR modeling tools toward the rational design of more efficient antibacterial agents. Particular emphasis is given to the setup of multitasking models along with ANNs aimed at jointly predicting different antibacterial activities and safety profiles of drugs/chem作者: GLIDE 時(shí)間: 2025-3-23 15:17
AutoWeka: Toward an Automated Data Mining Software for QSAR and QSPR Studies,tool that is powered by the widely used machine learning package Weka. The software provides a user-friendly graphical interface along with an automated parameter search capability. It employs two robust and popular machine learning methods: artificial neural networks and support vector machines. Th作者: 交響樂 時(shí)間: 2025-3-23 21:42
GENN: A GEneral Neural Network for Learning Tabulated Data with Examples from Protein Structure Pre was constructed using GENN. The source code and Linux executables for GENN are available from Research and Information Systems at . and from the Battelle Center for Mathematical Medicine at .. Bugs and problems with the GENN program should be reported to EF.作者: 糾纏,纏繞 時(shí)間: 2025-3-24 00:34
Using Neural Networks to Understand the Information That Guides Behavior: A Case Study in Visual Naes a compact holistic representation of the data and is thus an efficient way to encode a large set of views. Second, as we do not store the training views, we are not limited in the number of training views we use and the agent does not need to decide which views to learn.作者: 熔巖 時(shí)間: 2025-3-24 03:36 作者: 奇思怪想 時(shí)間: 2025-3-24 07:35 作者: 膽小鬼 時(shí)間: 2025-3-24 12:57
Neural Networks and Fuzzy Clustering Methods for Assessing the Efficacy of Microarray Based Intrinsiterature from three comprehensive experimental studies for distinguishing Luminal (A and B), Basal, Normal breast-like, and HER2 subtypes. Given the costly procedures involved in clinical studies, the proposed 93-gene set can be used for preliminary classification of breast cancer. Then, as a decis作者: 直覺好 時(shí)間: 2025-3-24 15:56 作者: Harbor 時(shí)間: 2025-3-24 22:08
Methods in Molecular Biologyhttp://image.papertrans.cn/b/image/162625.jpg作者: 揉雜 時(shí)間: 2025-3-25 00:15 作者: Halfhearted 時(shí)間: 2025-3-25 04:00
The Syphilitic as Moral Degeneratee range of structural factors, and the artificial neural network based TALOS-N program has been trained to extract backbone and side-chain torsion angles from .H, .N, and .C shifts. The program is quite robust and typically yields backbone torsion angles for more than 90 % of the residues and side-c作者: guardianship 時(shí)間: 2025-3-25 09:19
https://doi.org/10.1057/9780230375130een these microbial communities and their environment is essential for prediction of community structure, robustness, and response to ecosystem changes. Microbial Assemblage Prediction (MAP) describes microbial community structure as an artificial neural network (ANN) that models the microbial commu作者: 鳴叫 時(shí)間: 2025-3-25 15:01 作者: PIZZA 時(shí)間: 2025-3-25 18:10 作者: ARK 時(shí)間: 2025-3-25 22:38 作者: 約會 時(shí)間: 2025-3-26 03:25
https://doi.org/10.1057/9780230375130tivity by computational means can help us to understand their mechanism of action and deliver powerful drug-screening methodologies. In this chapter, we describe how to apply artificial neural networks to predict antimicrobial peptide activity.作者: motivate 時(shí)間: 2025-3-26 07:31 作者: 松馳 時(shí)間: 2025-3-26 11:08
https://doi.org/10.1057/9780230113497verse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In作者: Legend 時(shí)間: 2025-3-26 14:53
Stem Revision in Periprosthetic Fractures,ENN is in its generality, simplicity of use, and its specific handling of windowed input/output. Its main strength is its efficient handling of the input data, enabling learning from large datasets. GENN is built on a two-layered neural network and has the option to use separate inputs–output pairs 作者: 公式 時(shí)間: 2025-3-26 16:57 作者: minimal 時(shí)間: 2025-3-27 00:20
https://doi.org/10.1007/978-3-662-62954-3in the interpretation of medical images, either to help with lesion detection or to help determine if the lesion is benign or malignant. Artificial neural networks (ANNs) are usually employed to formulate the statistical models for computer analysis. Receiver operating characteristic curves are used作者: pulmonary 時(shí)間: 2025-3-27 04:29
Damian Griffin,Shanmugam Karthikeyanvantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability..This chapter describes the embedded implementation of a multi-biometric (作者: 別名 時(shí)間: 2025-3-27 07:13
Damian Griffin,Shanmugam Karthikeyans is to explore regularities within the information animals perceive during natural behavior. In this chapter, we describe how we have used artificial neural networks (ANNs) to explore efficiencies in vision and memory that might underpin visually guided route navigation in complex worlds. Specifica作者: 異教徒 時(shí)間: 2025-3-27 09:51
Bruno G. S. e Souza,Marc J. Philippontics, and, last but not least important, medicine. For example, in the therapy of Type 1 Diabetes (T1D), in which, for patient safety, glucose concentration in the blood should be maintained in a defined normoglycemic range, the ability to forecast glucose concentration in the short-term (with a pre作者: remission 時(shí)間: 2025-3-27 13:53
Klaus A. Siebenrock,Philipp Henlenge. Here we present the materials and techniques to deposit the layer stacks, define the structures, and etch the devices. In the end, we obtain tunnel junction devices exhibiting memristive switching for potential use as artificial synapses.作者: DEMN 時(shí)間: 2025-3-27 20:10
Femorokrurale Arterienverschlüsse recognition, prediction, and optimization. The ability of the human brain to learn in a fashion that tolerates noise and error has attracted many researchers and provided the starting point for the development of artificial neural networks: the intelligent systems. Intelligent systems can acclimati作者: Etymology 時(shí)間: 2025-3-27 22:34
Femorokrurale Arterienverschlüsses basic cluster patterns, more needs to be done to investigate the accuracy of clusters as well as to extract meaningful cluster characteristics and their relations to increase our confidence in their use in a clinical setting. In this study, an in-depth investigation of the efficacy of three report作者: Arbitrary 時(shí)間: 2025-3-28 04:25
Femorokrurale Arterienverschlüssebe and predict a particular activity/property of compounds. On the other hand, the Artificial Neural Network (ANN) is a tool that emulates the human brain to solve very complex problems. The exponential need for new compounds in the drug industry requires alternatives for experimental methods to dec作者: obsession 時(shí)間: 2025-3-28 09:22 作者: Accommodation 時(shí)間: 2025-3-28 12:33 作者: CUB 時(shí)間: 2025-3-28 17:18 作者: Galactogogue 時(shí)間: 2025-3-28 19:32 作者: 打算 時(shí)間: 2025-3-29 00:06 作者: 冷漠 時(shí)間: 2025-3-29 06:42 作者: 成績上升 時(shí)間: 2025-3-29 10:19 作者: 過份 時(shí)間: 2025-3-29 14:15 作者: Asperity 時(shí)間: 2025-3-29 18:02
Protein Structural Information Derived from NMR Chemical Shift with the Neural Network Program ,,e range of structural factors, and the artificial neural network based TALOS-N program has been trained to extract backbone and side-chain torsion angles from .H, .N, and .C shifts. The program is quite robust and typically yields backbone torsion angles for more than 90 % of the residues and side-c作者: 針葉 時(shí)間: 2025-3-29 19:58 作者: 逢迎春日 時(shí)間: 2025-3-30 02:47
A General ANN-Based Multitasking Model for the Discovery of Potent and Safer Antibacterial Agents,Given the prevalence of these microbial pathogens and their increasing resistance to existing antibiotics, there is a pressing need for new antibacterial drugs. However, development of a successful drug is a complex, costly, and time-consuming process. Quantitative Structure-Activity Relationships (作者: GET 時(shí)間: 2025-3-30 04:36
Use of Artificial Neural Networks in the QSAR Prediction of Physicochemical Properties and Toxicitir imported into the EU at levels of 1 tonne/year or more. This has meant an increase in the in silico prediction of such data. One of the chief predictive approaches is QSAR (quantitative structure–activity relationships), which is widely used in many fields..A QSAR approach that is increasingly bei作者: 危機(jī) 時(shí)間: 2025-3-30 10:08
Artificial Neural Network for Charge Prediction in Metabolite Identification by Mass Spectrometry,ir internal structure. Interpretation of experimental CID spectra always involves some form of in silico spectra of potential candidate molecules. Knowledge of how charge is distributed among fragments is an important part of CID simulations that generate in silico spectra from the chemical structur作者: 有抱負(fù)者 時(shí)間: 2025-3-30 16:14
Prediction of Bioactive Peptides Using Artificial Neural Networks,tivity by computational means can help us to understand their mechanism of action and deliver powerful drug-screening methodologies. In this chapter, we describe how to apply artificial neural networks to predict antimicrobial peptide activity.作者: Oscillate 時(shí)間: 2025-3-30 17:38
AutoWeka: Toward an Automated Data Mining Software for QSAR and QSPR Studies,d through a chemical intuition-driven trial-and-error process or via data-driven predictive modeling. The latter is based on the concept of quantitative structure-activity/property relationship (QSAR/QSPR) when applied in modeling the biological activity and chemical properties, respectively, of com作者: 一個(gè)姐姐 時(shí)間: 2025-3-31 00:18
Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In作者: 違抗 時(shí)間: 2025-3-31 04:14 作者: TRAWL 時(shí)間: 2025-3-31 05:41
Modulation of Grasping Force in Prosthetic Hands Using Neural Network-Based Predictive Control, with the electromechanical aspects of prosthetic devices present great challenges for precise control of this type of device. Model-based controllers may overcome this issue. Moreover, given the complexity of these kinds of electromechanical systems, neural network-based modeling arises as a good f作者: AXIOM 時(shí)間: 2025-3-31 09:55
Application of Artificial Neural Networks in Computer-Aided Diagnosis,in the interpretation of medical images, either to help with lesion detection or to help determine if the lesion is benign or malignant. Artificial neural networks (ANNs) are usually employed to formulate the statistical models for computer analysis. Receiver operating characteristic curves are used作者: cancellous-bone 時(shí)間: 2025-3-31 14:09
Developing a Multimodal Biometric Authentication System Using Soft Computing Methods,vantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability..This chapter describes the embedded implementation of a multi-biometric (
