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MAFFT version 5: improvement in accuracy of multiple sequence alignment

by Kazutaka Katoh, Kei-ichi Kuma, Hiroyuki Toh, Takashi Miyata - NUCLEIC ACIDS RES , 2005
"... The accuracy of multiple sequence alignment pro-gram MAFFT has been improved. The new version (5.3) of MAFFT offers new iterative refinement options, H-INS-i, F-INS-i and G-INS-i, in which pairwise alignment information are incorporated into objective function. These new options of MAFFT showed high ..."
Abstract - Cited by 801 (5 self) - Add to MetaCart
database. Such improvement was gen-erally observed for most methods, but remarkably large for the new options of MAFFT proposed here. Thus, we made a Ruby script, mafftE.rb, which aligns the input sequences together with their close homologues collected from SwissProt using NCBI-BLAST.

SPADE: An efficient algorithm for mining frequent sequences

by Mohammed J. Zaki - Machine Learning , 2001
"... Abstract. In this paper we present SPADE, a new algorithm for fast discovery of Sequential Patterns. The existing solutions to this problem make repeated database scans, and use complex hash structures which have poor locality. SPADE utilizes combinatorial properties to decompose the original proble ..."
Abstract - Cited by 437 (16 self) - Add to MetaCart
, and by an order of magnitude with some pre-processed data. It also has linear scalability with respect to the number of input-sequences, and a number of other database parameters. Finally, we discuss how the results of sequence mining can be applied in a real application domain.

Fitting a mixture model by expectation maximization to discover motifs in biopolymers.

by Timothy L Bailey , Charles Elkan - Proc Int Conf Intell Syst Mol Biol , 1994
"... Abstract The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expect~tiou ma.,dmization to fit a two-component finite mixture model to the set of sequences. Multiple motifs are found by fitting a mixture model to th ..."
Abstract - Cited by 947 (5 self) - Add to MetaCart
to the data, probabilistically erasing tile occurrences of the motif thus found, and repeating the process to find successive motifs. The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input. It returns a model of each motif and a threshold which

Large margin methods for structured and interdependent output variables

by Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun - JOURNAL OF MACHINE LEARNING RESEARCH , 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
Abstract - Cited by 624 (12 self) - Add to MetaCart
Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses

Algebraic laws for nondeterminism and concurrency

by Matthew Hennessy, Robin Milner - Journal of the ACM , 1985
"... Abstract. Since a nondeterministic and concurrent program may, in general, communicate repeatedly with its environment, its meaning cannot be presented naturally as an input/output function (as is often done in the denotational approach to semantics). In this paper, an alternative is put forth. Firs ..."
Abstract - Cited by 608 (13 self) - Add to MetaCart
Abstract. Since a nondeterministic and concurrent program may, in general, communicate repeatedly with its environment, its meaning cannot be presented naturally as an input/output function (as is often done in the denotational approach to semantics). In this paper, an alternative is put forth

Additive Logistic Regression: a Statistical View of Boosting

by Jerome Friedman, Trevor Hastie, Robert Tibshirani - Annals of Statistics , 1998
"... Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often be dramatically improved by sequentially applying them to reweighted versions of the input dat ..."
Abstract - Cited by 1750 (25 self) - Add to MetaCart
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often be dramatically improved by sequentially applying them to reweighted versions of the input

Controlled and automatic human information processing

by Walter Schneider, Richard M. Shiffrin - I. Detection, search, and attention. Psychological Review , 1977
"... A two-process theory of human information processing is proposed and applied to detection, search, and attention phenomena. Automatic processing is activa-tion of a learned sequence of elements in long-term memory that is initiated by appropriate inputs and then proceeds automatically—without subjec ..."
Abstract - Cited by 874 (16 self) - Add to MetaCart
A two-process theory of human information processing is proposed and applied to detection, search, and attention phenomena. Automatic processing is activa-tion of a learned sequence of elements in long-term memory that is initiated by appropriate inputs and then proceeds automatically

A NEW POLYNOMIAL-TIME ALGORITHM FOR LINEAR PROGRAMMING

by N. Karmarkar - COMBINATORICA , 1984
"... We present a new polynomial-time algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than the ell ..."
Abstract - Cited by 860 (3 self) - Add to MetaCart
We present a new polynomial-time algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than

The Nature and Growth of Vertical Specialization in World Trade

by David Hummels - Journal of International Economics
"... Abstract: Dramatic changes are occurring in the nature of international trade. Production processes increasingly involve a sequential, vertical trading chain stretching across many countries, with each country specializing in particular stages of a good’s production sequence. We document a key aspe ..."
Abstract - Cited by 481 (20 self) - Add to MetaCart
Abstract: Dramatic changes are occurring in the nature of international trade. Production processes increasingly involve a sequential, vertical trading chain stretching across many countries, with each country specializing in particular stages of a good’s production sequence. We document a key

(a) Input sequence (b) Motion magnified sequence

by Ce Liu, Antonio Torralba, William T. Freeman, Frédo Durand, Edward H. Adelson
"... Figure 1: Frames from input and motion magnified output sequence. The algorithm groups the input (a) into motion layers and amplifies the motions of a layer selected by the user. Deformations of the swing support elements are revealed in the motion magnified output sequence (b), magnifying the origi ..."
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Figure 1: Frames from input and motion magnified output sequence. The algorithm groups the input (a) into motion layers and amplifies the motions of a layer selected by the user. Deformations of the swing support elements are revealed in the motion magnified output sequence (b), magnifying
Results 1 - 10 of 9,457