The data available during the drug discovery process is vast in amount and diverse in nature. To gain useful information from such data, an effective visualisation tool is required. To provide better visualisation facilities to the domain experts (screening scientist, biologist, chemist, etc.),we developed a software which is based on recently developed principled visualisation algorithms such as Generative Topographic Mapping (GTM) and Hierarchical Generative Topographic Mapping (HGTM). The software also supports conventional visualisation techniques such as Principal Component Analysis, NeuroScale, PhiVis, and Locally Linear Embedding (LLE). The software also provides global and local regression facilities . It supports regression algorit...
Cette thèse concerne l'utilisation de Cartographie Topographique Générative (Generative Topographie ...
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar ...
Hierarchical visualization systems are desirable because a single twodimensional visualization plot ...
Today, the data available to tackle many scientific challenges is vast in quantity and diverse in na...
This thesis introduces a flexible visual data exploration framework which combines advanced projecti...
This thesis applies a hierarchical latent trait model system to a large quantity of data. The motiva...
Today, the data available to tackle many scientific challenges is vast in quantity and diverse in na...
Analysing the molecular polymorphism and interactions of DNA, RNA and proteins is of fundamental imp...
Solving many scientific problems requires effective regression and/or classification models for larg...
The popularity of machine learning (ML) across drug discovery continues to grow, yielding impressive...
YesThe early diagnosis and personalised treatment of diseases are facilitated by machine learning. T...
In drug discovery, domain experts from different fields such as medicinal chemistry, biology, and co...
Data visualization algorithms and feature selection techniques are both widely used in bioinformatic...
This thesis concerns the application of the Generative Topographic Mapping (GTM) approach to the ana...
International audienceThe previously reported procedure to generate “universal” Generative Topograph...
Cette thèse concerne l'utilisation de Cartographie Topographique Générative (Generative Topographie ...
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar ...
Hierarchical visualization systems are desirable because a single twodimensional visualization plot ...
Today, the data available to tackle many scientific challenges is vast in quantity and diverse in na...
This thesis introduces a flexible visual data exploration framework which combines advanced projecti...
This thesis applies a hierarchical latent trait model system to a large quantity of data. The motiva...
Today, the data available to tackle many scientific challenges is vast in quantity and diverse in na...
Analysing the molecular polymorphism and interactions of DNA, RNA and proteins is of fundamental imp...
Solving many scientific problems requires effective regression and/or classification models for larg...
The popularity of machine learning (ML) across drug discovery continues to grow, yielding impressive...
YesThe early diagnosis and personalised treatment of diseases are facilitated by machine learning. T...
In drug discovery, domain experts from different fields such as medicinal chemistry, biology, and co...
Data visualization algorithms and feature selection techniques are both widely used in bioinformatic...
This thesis concerns the application of the Generative Topographic Mapping (GTM) approach to the ana...
International audienceThe previously reported procedure to generate “universal” Generative Topograph...
Cette thèse concerne l'utilisation de Cartographie Topographique Générative (Generative Topographie ...
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar ...
Hierarchical visualization systems are desirable because a single twodimensional visualization plot ...