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P Baldi

Publications and source records attributed to P Baldi.

14 recordsLinked to original sources
PubMed1996

Naturally occurring nucleosome positioning signals in human exons and introns.

We describe the structural implications of a periodic pattern found in human exons and introns by hidden Markov models. We show that exons (besides the reading frame) have a specific sequential structure in the form of a pattern with triplet consensus non-T(A/T)G, and a minimal periodicity of roughly ten nucleotides. The periodic pattern is also present in intron sequences, although the strength per nucleotide is weaker. Using two independent profile methods based on triplet bendability parameters from DNase I experiments and nucleosome positioning data, we show that the pattern in multiple alignments of internal exon and intron sequences corresponds to a periodic "in phase" bending potential towards the major groove of the DNA. The nucleosome positioning data show that the consensus triplets (and their complements) have a preference for locations on a bent double helix where the major groove faces inward and is compressed. The in-phase triplets are located adjacent to GCC/GGC triplets known to have the strongest bias in their positioning on the nuclesome. Analysis of mRNA sequences encoding proteins with known tertiary structure exclude the possibility that the pattern is a consequence of the previously well-known periodicity caused by the encoding of alpha-helices in proteins. Finally, we discuss the relation between the bending potential of coding and non-coding regions and its impact on the translational positioning of nucleosomes and the recognition of genes by the transcriptional machinery.

Base Sequence↗
PubMed1996

Hybrid modeling, HMM/NN architectures, and protein applications.

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. We develop the approach for the case of Hidden Markov Models (HMMs), by deriving a class of hybrid HMM/NN architectures. These architectures can be trained with unified algorithms that blend HMM dynamic programming with NN backpropagation. In the case of complex data, mixtures of HMMs or modulated HMMs must be used. NNs can then be applied both to the parameters of each single HMM, and to the switching or modulatation of the models, as a function of input or context. Hybrid HMM/NN architectures provide a flexible NN parameterization for the control of model structure and complexity. At the same time, they can capture distributions that, in practice, are inaccessible to single HMMs. The HMM/NN hybrid approach is tested, in its simplest form, by constructing a model of the immunoglobulin protein family. A hybrid model is trained, and a multiple alignment derived, with less than a fourth of the number of parameters used with previous single HMMs.

Algorithms↗
PubMed1996

Characterization of prokaryotic and eukaryotic promoters using hidden Markov models.

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 promoters are divided into a number of different classes, depending on which polymerase-associated factors that bind to them. We find that HMMs trained on such subclasses of Escherichia coli promoters (specifically, the so-called sigma 70 and sigma 54 classes) give an excellent classification of unknown promoters with respect to sigma-class. HMMs trained on eukaryotic sequences from human genes also model nicely all the essential well known signals, in addition to a potentially new signal upstream of the TATA-box. We furthermore employ a novel technique for automatically discovering different classes in the input data (the promoters) using a system of self-organizing parallel HMMs. These self-organizing HMMs have at the same time the ability to find clusters and the ability to model the sequential structure in the input data. This is highly relevant in situations where the variance in the data is high, as is the case for the subclass structure in for example promoter sequences.

Escherichia coli↗
PubMed1995

Substitution matrices and hidden Markov models.

Hidden Markov models (HMMs) provide a general framework for expressing primary sequence consensus. HMMs can effectively be used to model and align protein families, and to search data bases. HMMs, however, have a large number of parameters. When only few sequences are available for model fitting, additional prior information must be incorporated into the models. We derive a simple algorithm that directly incorporates prior information provided by substitution matrices into the HMM learning procedure.

Algorithms↗
PubMed1995

Periodic sequence patterns in human exons.

We analyse the sequential structure of human exons and their flanking introns by hidden Markov models. Together, models of donor site regions, acceptor site regions and flanked internal exons, show that exons--besides the reading frame--hold a specific periodic pattern. The pattern, which has the consensus: non-T(A/T)G and a minimal periodicity of roughly 10 nucleotides, is not a consequence of the nucleotide statistics in the three codon positions, nor of the well known nucleosome positioning signal. We discuss the relation between the pattern and other known sequence elements responsible for the intrinsic bending or curvature of DNA.

Base Sequence↗
PubMed1995

Protein modeling with hybrid Hidden Markov Model/neural network architectures.

Hidden Markov Models (HMMs) are useful in a number of tasks in computational molecular biology, and in particular to model and align protein families. We argue that HMMs are somewhat optimal within a certain modeling hierarchy. Single first order HMMs, however, have two potential limitations: a large number of unstructured parameters, and a built-in inability to deal with long-range dependencies. Hybrid HMM/Neural Network (NN) architectures attempt to overcome these limitations. In hybrid HMM/NN, the HMM parameters are computed by a NN. This provides a reparametrization that allows for flexible control of model complexity, and incorporation of constraints. The approach is tested on the immunoglobulin family. A hybrid model is trained, and a multiple alignment derived, with less than a fourth of the number of parameters used with previous single HMMs. To capture dependencies, however, one must resort to a larger hybrid model class, where the data is modeled by multiple HMMs. The parameters of the HMMs, and their modulation as a function of input or context, is again calculated by a NN.

Amino Acid Sequence↗
PubMed1994

Hidden Markov models of biological primary sequence information.

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 of the models from the examples in a given family. The HMM approach is applied to three protein families: globins, immunoglobulins, and kinases. In all cases, the models derived capture the important statistical characteristics of the family and can be used for a number of tasks, including multiple alignments, motif detection, and classification. For K sequences of average length N, this approach yields an effective multiple-alignment algorithm which requires O(KN2) operations, linear in the number of sequences.

Algorithms↗
PubMed1994

Hidden Markov Models of the G-protein-coupled receptor family.

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 set comprising 142 sequences. The resulting model is shown to perform well on a number of tasks, including multiple alignments, discrimination, large data base searches, classification, and fragment detection. General analytical results on the expectation and standard deviation of the likelihood of random sequences are also presented.

Algorithms↗
PubMed1988

How sensory maps could enhance resolution through ordered arrangements of broadly tuned receivers.

We investigate the properties of a model recently introduced by Heiligenberg (1987) for an array of sensors tuned to progressively higher ranges of a continuous stimulus variable x and with bell shaped single response curve with width parameter d. The main result is that as d increases, the overall response rapidly becomes almost linear in a very smooth and robust fashion. Biological relevance and implications of the model and of its extensions are discussed together with a few examples.

Mathematics↗
PubMed1984

[Treatment of large tumors of the cerebellopontile angle using a combined transtentorial and translabyrinthine approach to the middle cranial fossa].

The Authors have reported on 7 patients with large tumors (larger than 4 cm) of the cerebello-pontine angle operated-on utilizing a subtemporal-transtentorial-translabyrinthine-trans-occipital approach. The technique, the results and complications of this approach to the cerebello-pontine angle are discussed. The advantages are the delineation of the cranial nerves and of the ventrolateral brainstem with its blood supply. This approach has been associated with a low morbidity and no operative mortality in 5 cases of acoustic nerve tumor and 2 meningiomas.

Adolescent↗
PubMedDate not supplied

[Therapy of idiopathic thrombocytopenic purpura].

Various treatment strategies for acute and chronic idiopathic thrombocytopenic purpura (ITP) in childhood are reviewed. In acute ITP steroids induce a prompt improvement of symptoms and a rapid increase in platelet count; the use of high dose intravenous immunoglobulin is a valid alternative treatment to steroids. In chronic ITP splenectomy is still the most successful treatment, as it induces remission in 60-80% of patients. The risk for severe infections after splenectomy is still considerable in children; therefore other treatment schedules are suggested (i.v. immunoglobulin, courses of steroids, high dose methylprednisolone). In this paper we report 100 pediatric cases with acute ITP and 36 with chronic ITP.

Acute Disease↗