Results 11 
15 of
15
Finding Precursor Compounds in Secondary Metabolism
 Genome Informatics
, 1999
"... A precursor is a compound which is transformed to a class of functional molecules within short steps. It is an important process in the production of natural drugs to decide whether a given compound is a precursor or not. We present two strategies to select precursor compounds in the secondary me ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
A precursor is a compound which is transformed to a class of functional molecules within short steps. It is an important process in the production of natural drugs to decide whether a given compound is a precursor or not. We present two strategies to select precursor compounds in the secondary metabolism of terpenoids: one is to find the packing of basic molecules in the given cyclic structure, and the other is to find the synthetic map of the given set of compounds. Both strategies play important roles in reproducing tracer experiments on a computer. 1 Introduction Finding the biosynthetic pathway of a hormone or a natural drug is the key issue for its industrial production. Even a limited increase in its production rate may lead to a drastic change in the synthetic scheme at a commercial level, because of its very low yield from raw materials. For example, the average yield of paclitaxel (a recently approved anticancer drug) from the yew bark is in the range of 0.0140.017%. ...
Global Inference and Learning Algorithms for MultiLingual Dependency Parsing. Unpublished manuscript
, 2007
"... This paper gives an overview of the work of McDonald et al. (McDonald et al. 2005a, 2005b; McDonald and Pereira 2006; McDonald et al. 2006) on global inference and learning algorithms for datadriven dependency parsing. Further details can be found in the thesis of McDonald (McDonald 2006). This pap ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
This paper gives an overview of the work of McDonald et al. (McDonald et al. 2005a, 2005b; McDonald and Pereira 2006; McDonald et al. 2006) on global inference and learning algorithms for datadriven dependency parsing. Further details can be found in the thesis of McDonald (McDonald 2006). This paper is primarily intended for the audience of the ESSLLI 2007 course on datadriven dependency parsing. 1.
Several geometric data structures for objects in the plane can be constructed using persistent binary search trees. (I know, I promised I wouldn't do much geometry, but this was sort of irresistible.)
"... ach insertion or deletion crates a new version of T y ; we attach each version to the corresponding leaf in T x . The overall preprocessing time is O(n log n), and the overall space is O(n). To answer a query for point (a; b), we search for a in T x to nd the correct version of T y , and then sear ..."
Abstract
 Add to MetaCart
ach insertion or deletion crates a new version of T y ; we attach each version to the corresponding leaf in T x . The overall preprocessing time is O(n log n), and the overall space is O(n). To answer a query for point (a; b), we search for a in T x to nd the correct version of T y , and then search that version of T y for the successor of b. The query time in each tree is O(log n), so the overall query time is also O(log n). (b) Modify the previous data structure to store a set of n disjoint nonhorizontal segments, with the same preprocessing, space, and query bounds. [Hint: Use a persistent kinetic binary search tree.] Solution: A fulledged kinetic data structure is overkill here. The only necessary change from part (a) is that we store the line equations of segments in T y . Whenever we search T y , either to locate a point (a; b) or to insert a new segment with left endpoint (a; b), we replace every direct comparison with b with a test whether (a; b) is above or below a lin
www.inescc.pt SOME COMPUTATIONAL IMPROVEMENTS ON FINDING THE K SHORTEST SPANNING TREES
, 2008
"... Abstract: A key computational step in the K shortest spanning tree problem is the procedure to obtain the second best. In this paper we describe and implement several methods for the determination of the second shortest tree on a network. The methods use different strategies for reaching the best sw ..."
Abstract
 Add to MetaCart
Abstract: A key computational step in the K shortest spanning tree problem is the procedure to obtain the second best. In this paper we describe and implement several methods for the determination of the second shortest tree on a network. The methods use different strategies for reaching the best swap of edges that leads to the second best spanning tree. Several fathoming conditions are considered in order to prevent useless calculations. Computational experiments are presented and results are analysed for randomly generated networks.
reports/55 Spanning Tree Methods for Discriminative Training of Dependency Parsers
"... Untyped dependency parsing can be viewed as the problem of finding maximum spanning trees (MSTs) in directed graphs. Using this representation, the Eisner (1996) parsing algorithm is sufficient for searching the space of projective trees. More importantly, the representation is extended naturally to ..."
Abstract
 Add to MetaCart
Untyped dependency parsing can be viewed as the problem of finding maximum spanning trees (MSTs) in directed graphs. Using this representation, the Eisner (1996) parsing algorithm is sufficient for searching the space of projective trees. More importantly, the representation is extended naturally to nonprojective parsing using ChuLiuEdmonds (Chu and Liu, 1965; Edmonds, 1967) MST algorithm. These efficient parse search methods support largemargin discriminative training methods for learning dependency parsers. We evaluate these methods experimentally on the English and Czech treebanks. 1