ACM DL

Knowledge Discovery from Data (TKDD)

Menu

Search Issue
enter search term and/or author name

Archive


ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 2 Issue 1, March 2008

Introduction to special issue on bioinformatics
Mohammed J. Zaki, George Karypis, Jiong Yang, Wei Wang
Article No.: 1
DOI: 10.1145/1342320.1342321

Compositional mining of multirelational biological datasets
Ying Jin, T. M. Murali, Naren Ramakrishnan
Article No.: 2
DOI: 10.1145/1342320.1342322

High-throughput biological screens are yielding ever-growing streams of information about multiple aspects of cellular activity. As more and more categories of datasets come online, there is a corresponding multitude of ways in which inferences...

Discovering semantic biomedical relations utilizing the Web
Saurav Sahay, Sougata Mukherjea, Eugene Agichtein, Ernest V. Garcia, Shamkant B. Navathe, Ashwin Ram
Article No.: 3
DOI: 10.1145/1342320.1342323

To realize the vision of a Semantic Web for Life Sciences, discovering relations between resources is essential. It is very difficult to automatically extract relations from Web pages expressed in natural language formats. On the other hand,...

Developmental stage annotation of Drosophila gene expression pattern images via an entire solution path for LDA
Jieping Ye, Jianhui Chen, Ravi Janardan, Sudhir Kumar
Article No.: 4
DOI: 10.1145/1342320.1342324

Gene expression in a developing embryo occurs in particular cells (spatial patterns) in a time-specific manner (temporal patterns), which leads to the differentiation of cell fates. Images of a Drosophila melanogaster embryo at a given...

Adaptive discriminant analysis for microarray-based classification
Yijuan Lu, Qi Tian, Jennifer Neary, Feng Liu, Yufeng Wang
Article No.: 5
DOI: 10.1145/1342320.1342325

Microarray technology has generated enormous amounts of high-dimensional gene expression data, providing a unique platform for exploring gene regulatory networks. However, the curse of dimensionality plagues effort to analyze these high throughput...

A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology
Kosuke Hashimoto, Kiyoko Flora Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka
Article No.: 6
DOI: 10.1145/1342320.1342326

Mining frequent patterns from large datasets is an important issue in data mining. Recently, complex and unstructured (or semi-structured) datasets have appeared as targets for major data mining applications, including text mining, web mining and...