摘要:
Provided is an information processing apparatus including an estimation unit that expresses a light intensity distribution, which is obtained by irradiating light to a measurement object of a measurement target having a plurality of substances with mutually different responsive characteristics to the light on a surface and/or an inside of the measurement object, as a linear combination of light intensity distributions, which are obtained by irradiating the light to reference measurement objects, each of which has a single substance, models the light intensity distribution obtained from each of the reference measurement objects so as to follow a predetermined probability distribution, and estimates a combination coefficient of the linear combination from the light intensity distribution obtained from the measurement object of the measurement target.
摘要:
Provided is an information processing apparatus including an estimation unit that expresses a light intensity distribution, which is obtained by irradiating light to a measurement object of a measurement target having a plurality of substances with mutually different responsive characteristics to the light on a surface and/or an inside of the measurement object, as a linear combination of light intensity distributions, which are obtained by irradiating the light to reference measurement objects, each of which has a single substance, models the light intensity distribution obtained from each of the reference measurement objects so as to follow a predetermined probability distribution, and estimates a combination coefficient of the linear combination from the light intensity distribution obtained from the measurement object of the measurement target.
摘要:
Disclosed herein is an evaluation predicting device including: an estimating section configured to define a plurality of first latent vectors, a plurality of second latent vectors, evaluation values, a plurality of first feature vectors, a plurality of second feature vectors, a first projection matrix, and a second projection matrix, express the first latent vectors and the second latent vectors, and perform Bayesian estimation with the first feature vectors, the second feature vectors, and a known the evaluation value as learning data, and calculate a posterior distribution of a parameter group including the first latent vectors, the second latent vectors, the first projection matrix, and the second projection matrix; and a predicting section configured to calculate a distribution of an unknown the evaluation value on a basis of the posterior distribution of the parameter group.
摘要:
A highly homogeneous library can be obtained by cleaving a genomic DNA by a sequence-independent cleavage method, such as sonication. By selecting satellite sequences from such a library, efficiency of isolation is improved. Thus, an efficient method of isolating microsatellite sequences, which are useful as DNA markers, is provided.