Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 1 -
9 of
9
Ultraconservative Online Algorithms for Multiclass Problems
- Journal of Machine Learning Research
, 2001
"... In this paper we study online classification algorithms for multiclass problems in the mistake bound model. The hypotheses we use maintain one prototype vector per class. Given an input instance, a multiclass hypothesis computes a similarity-score between each prototype and the input instance and th ..."
Abstract
-
Cited by 320 (21 self)
- Add to MetaCart
and then sets the predicted label to be the index of the prototype achieving the highest similarity. To design and analyze the learning algorithms in this paper we introduce the notion of ultraconservativeness. Ultraconservative algorithms are algorithms that update only the prototypes attaining similarity
Unconfused Ultraconservative Multiclass Algorithms
"... We tackle the problem of learning linear classifiers from noisy datasets in a multiclass setting. The two-class version of this problem was studied a few years ago by, e.g. Bylander (1994) and Blum et al. (1996): in these contributions, the proposed approaches to fight the noise revolve around a Per ..."
Abstract
- Add to MetaCart
Perceptron learning scheme fed with peculiar examples computed through a weighted average of points from the noisy training set. We propose to build upon these approaches and we introduce a new algorithm called UMA (for Unconfused Multiclass additive Algorithm) which may be seen as a generalization
Peptide Vocabulary Analysis Reveals Ultra-Conservation and Homonymity in Protein Sequences
"... Abstract: A new algorithm is presented for vocabulary analysis (word detection) in texts of human origin. It performs at 60%–70 % overall accuracy and greater than 80 % accuracy for longer words, and approximately 85 % sensitivity on Alice in Wonderland, a considerable improvement on previous method ..."
Abstract
- Add to MetaCart
Abstract: A new algorithm is presented for vocabulary analysis (word detection) in texts of human origin. It performs at 60%–70 % overall accuracy and greater than 80 % accuracy for longer words, and approximately 85 % sensitivity on Alice in Wonderland, a considerable improvement on previous
BMC Bioinformatics BioMed Central Methodology article Multiple organism algorithm for finding ultraconserved elements
, 2008
"... This is an Open Access article distributed under the terms of the Creative Commons Attribution License ..."
Abstract
- Add to MetaCart
This is an Open Access article distributed under the terms of the Creative Commons Attribution License
ORIGINAL RESEARCH Peptide Vocabulary Analysis Reveals Ultra-Conservation and Homonymity in Protein Sequences
"... Abstract: A new algorithm is presented for vocabulary analysis (word detection) in texts of human origin. It performs at 60%–70 % overall accuracy and greater than 80 % accuracy for longer words, and approximately 85 % sensitivity on Alice in Wonderland, a considerable improvement on previous method ..."
Abstract
- Add to MetaCart
Abstract: A new algorithm is presented for vocabulary analysis (word detection) in texts of human origin. It performs at 60%–70 % overall accuracy and greater than 80 % accuracy for longer words, and approximately 85 % sensitivity on Alice in Wonderland, a considerable improvement on previous
i-ADHoRe 3.0–fast and sensitive detection of genomic homology in extremely large data sets
- Nucleic Acids Res
, 2012
"... Comparative genomics is a powerful means to gain insight into the evolutionary processes that shape the genomes of related species. As the number of sequenced genomes increases, the development of software to perform accurate cross-species analyses becomes indispensable. However, many implementation ..."
Abstract
-
Cited by 4 (0 self)
- Add to MetaCart
and gene order (collinearity), i-ADHoRe 3.0, and its application to eukaryotic genomes. The use of efficient algorithms and support for parallel computing enable the analysis of large-scale data sets. Unlike other tools, i-ADHoRe can process the Ensembl data set, con-taining 49 species, in 1 h. Furthermore
NcDNAlign: Plausible Multiple Alignments of Non-Protein-Coding Genomic Sequences
"... Genome-wide multiple sequence alignments (MSAs) are a necessary prerequisite for an increasingly diverse collection of comparative genomic approaches. Here we present a versatile method that generates high-quality MSAs for non-protein-coding sequences. The NcDNAlign pipeline combines pairwise BLAST ..."
Abstract
- Add to MetaCart
alignments. A showcase application of bacterial ncRNA prediction based on alignments of both algorithms results in similar sensitivity, false discovery rates and up to hundred putatively novel ncRNA structures. Similar findings hold for our application of NcDNAlign to the identification of ultra-conserved
SOFTWARE ARTICLE Open Access WordCluster: detecting clusters of DNA words and genomic elements
"... Background: Many k-mers (or DNA words) and genomic elements are known to be spatially clustered in the genome. Well established examples are the genes, TFBSs, CpG dinucleotides, microRNA genes and ultra-conserved non-coding regions. Currently, no algorithm exists to find these clusters in a statisti ..."
Abstract
- Add to MetaCart
Background: Many k-mers (or DNA words) and genomic elements are known to be spatially clustered in the genome. Well established examples are the genes, TFBSs, CpG dinucleotides, microRNA genes and ultra-conserved non-coding regions. Currently, no algorithm exists to find these clusters in a
Sequence analysis Seed-based INTARNA prediction combined with GFP-reporter system identifies mRNA targets of the small RNA Yfr1
"... Motivation: Prochlorococcus possesses the smallest genome of all sequenced photoautotrophs. Although the number of regulatory proteins in the genome is very small, the relative number of small regulatory RNAs is comparable with that of other bacteria. The compact genome size of Prochlorococcus offer ..."
Abstract
- Add to MetaCart
offers an ideal system to search for targets of small RNAs (sRNAs) and to refine existing target prediction algorithms. Results: Target predictions for the cyanobacterial sRNA Yfr1 were carried out with INTARNA in Prochlorococcus MED4. The ultraconserved Yfr1 sequence motif was defined as the putative
