Better 1D predictions by experts with machines.
نویسنده
چکیده
Accuracy of predicting protein secondary structure and solvent accessibility has been improved significantly by using evolutionary information contained in multiple sequence alignments. For the second Asilomar meeting, predictions were made automatically for all targets using the publicly available prediction service PredictProtein. Additionally, a semiautomatic procedure for generating more informative alignments was used in combination with the PHD prediction methods. Results confirmed the estimates for prediction accuracy. Furthermore, the more informative alignments yielded better predictions. The fairly accurate predictions of 1D structure were successfully used by various groups for the Asilomar meeting as first step toward predicting higher dimensions of protein structure.
منابع مشابه
Making Business Predictions by Combining Human and Machine Intelligence in Prediction Markets
Computers can use vast amounts of data to make predictions that are often more accurate than those by human experts. Yet, humans are more adept at processing unstructured information and at recognizing unusual circumstances and their consequences. Can we combine predictions from humans and machines to get predictions that are better than either could do alone? We used prediction markets to comb...
متن کاملCombining Human and Machine Intelligence
An extensive literature in psychology, economics, statistics, operations research and management science has dealt with comparing forecasts based on human-expert judgment vs. (statistical) models in a variety of scenarios, mostly finding advantage of the latter, yet acknowledging the necessity of the former. Although computers can use vast amounts of data to make predictions that are often more...
متن کاملImproving Simulation Accuracy of a Downsized Turbocharged SI Engine by Developing a Predictive Combustion Model in 1D Simulation Software
In this paper we aim to develop a predictive combustion model for a turbocharged engine in GT-Power software to better simulate engine characteristics and study its behavior under variety of conditions. Experimental data from combustion was initially being used for modelling combustion in software and these data were used for model calibration and result validation. EF7-TC engine was chosen for...
متن کاملHybrid system for protein secondary structure prediction.
We have developed a hybrid system to predict the secondary structures (alpha-helix, beta-sheet and coil) of proteins and achieved 66.4% accuracy, with correlation coefficients of C(coil) = 0.429, C alpha = 0.470 and C beta = 0.387. This system contains three subsystems ("experts"): a neural network module, a statistical module and a memory-based reasoning module. First, the three experts indepe...
متن کاملIntegrating binding site predictions using meta classification methods
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. There is good reason to believe that predictions from these different classes of algorithms could be used in conjunction to improve the quality of predictions. In this paper, we apply single layer networks and support vector machines on predictions from key algorithms. Furthermore, w...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Proteins
دوره Suppl 1 شماره
صفحات -
تاریخ انتشار 1997