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- Pierre Baldi, SÃ¸ren Brunak, Yves Chauvin, Claus A. F. Andersen, Henrik Nielsen
- Bioinformatics
- 2000

We provide a unified overview of methods that currently are widely used to assess the accuracy of prediction algorithms, from raw percentages, quadratic error measures and other distances, andâ€¦ (More)

- P. Baldi, Yves Chauvin, Tim Hunkapiller, Megan McClure
- Proceedings of the National Academy of Sciencesâ€¦
- 1994

Hidden Markov model (HMM) techniques are used to model families of biological sequences. A smooth and convergent algorithm is introduced to iteratively adapt the transition and emission parameters ofâ€¦ (More)

- Pierre Baldi, Yves Chauvin
- Neural Computation
- 1994

A simple learning algorithm for Hidden Markov Models (HMMs) is presented together with a number of variations. Unlike other classical algorithms such as the Baum-Welch algorithm, the algorithmsâ€¦ (More)

- Anders Gorm Pedersen, Pierre Baldi, Yves Chauvin, SÃ¸ren Brunak
- Computers & Chemistry
- 1999

Computational prediction of eukaryotic promoters from the nucleotide sequence is one of the most attractive problems in sequence analysis today, but it is also a very difficult one. Thus, currentâ€¦ (More)

- P. Baldi, Yves Chauvin
- Neural computation
- 1996

We describe a hybrid modeling approach where the parameters of a mode are calculated and modulated by another model, typically a neural network (NN), to avoid both overfitting and underfitting. Weâ€¦ (More)

In this paper we utilize hidden Markov models (HMMs) and information theory to analyze prokaryotic and eukaryotic promoters. We perform this analysis with special emphasis on the fact that promotersâ€¦ (More)

- A. Gersel Pedersen, P. Baldi, Yves Chauvin, Soren Brunak
- Journal of molecular biology
- 1998

The fact that DNA three-dimensional structure is important for transcriptional regulation begs the question of whether eukaryotic promoters contain general structural features independently of whatâ€¦ (More)

- Yves Chauvin
- NIPS
- 1988

This paper presents a variation of the back-propagation algorithm that makes optimal use of a network hidden units by decr~asing an "energy" term written as a function of the squared activations ofâ€¦ (More)

- Pierre Baldi, Yves Chauvin
- Neural Computation
- 1993

After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs anâ€¦ (More)

- Pierre Baldi, Yves Chauvin
- Journal of Computational Biology
- 1994

Hidden Markov Model techniques are used to derive a new model of the G-protein-coupled receptor family. The transition and emission parameters of the model are adjusted using a training setâ€¦ (More)