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Feature selection plays an undeniably important role in classification problems involving high dimensional datasets such as microarray datasets. For filter-based feature selection, two well-known criteria used...
Citation: Algorithms for Molecular Biology 2007 2:7
Genome-wide screens for structured ncRNA genes in mammals, urochordates, and nematodes have predicted thousands of putative ncRNA genes and other structured RNA motifs. A prerequisite for their functional anno...
Citation: Algorithms for Molecular Biology 2007 2:6
One-dimensional (1-D) electrophoretic data obtained using the cDNA-AFLP method have attracted great interest for the identification of differentially expressed transcript-derived fragments (TDFs). However, hig...
Citation: Algorithms for Molecular Biology 2007 2:5
Citation: Algorithms for Molecular Biology 2007 2:4
Understanding the protein folding mechanism remains a grand challenge in structural biology. In the past several years, computational theories in molecular dynamics have been employed to shed light on the fold...
Citation: Algorithms for Molecular Biology 2007 2:3
Transcriptional regulatory network (TRN) discovery from one method (e.g. microarray analysis, gene ontology, phylogenic similarity) does not seem feasible due to lack of sufficient information, resulting in th...
Citation: Algorithms for Molecular Biology 2007 2:2
When transcription factor binding sites are known for a particular transcription factor, it is possible to construct a motif model that can be used to scan sequences for additional sites. However, few statisti...
Citation: Algorithms for Molecular Biology 2007 2:1
Simulation methods can assist in describing and understanding complex networks of interacting proteins, providing fresh insights into the function and regulation of biological systems. Recent studies have inve...
Citation: Algorithms for Molecular Biology 2006 1:25
The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically evaluate a novel clustering technique for clu...
Citation: Algorithms for Molecular Biology 2006 1:24
The main goal of the motif finding problem is to detect novel, over-represented unknown signals in a set of sequences (e.g. transcription factor binding sites in a genome). The most widely used algorithms for ...
Citation: Algorithms for Molecular Biology 2006 1:23
A structured motif allows variable length gaps between several components, where each component is a simple motif, which allows either no gaps or only fixed length gaps. The motif can either be represented as a p...
Citation: Algorithms for Molecular Biology 2006 1:22
Extracting motifs from sequences is a mainstay of bioinformatics. We look at the problem of mining structured motifs, which allow variable length gaps between simple motif components. We propose an efficient a...
Citation: Algorithms for Molecular Biology 2006 1:21
A new, promising solvent exposure measure, called half-sphere-exposure (HSE), has recently been proposed. Here, we study the reconstruction of a protein's C α trace solely fr...
Citation: Algorithms for Molecular Biology 2006 1:20
The performance of alignment programs is traditionally tested on sets of protein sequences, of which a reference alignment is known. Conclusions drawn from such protein benchmarks do not necessarily hold for t...
Citation: Algorithms for Molecular Biology 2006 1:19
The use of Chaos Game Representation (CGR) or its generalization, Universal Sequence Maps (USM), to describe the distribution of biological sequences has been found objectionable because of the fractal structu...
Citation: Algorithms for Molecular Biology 2006 1:18
In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is ...
Citation: Algorithms for Molecular Biology 2006 1:17
A number of algorithms have been developed for calculating the quartet distance between two evolutionary trees on the same set of species. The quartet distance is the number of quartets – sub-trees induced by ...
Citation: Algorithms for Molecular Biology 2006 1:16
Biclustering has emerged as a powerful algorithmic tool for analyzing measurements of gene expression. A number of different methods have emerged for computing biclusters in gene expression data. Many of these...
Citation: Algorithms for Molecular Biology 2006 1:15
An important challenge in eukaryotic gene prediction is accurate identification of alternatively spliced exons. Functional transcripts can go undetected in gene expression studies when alternative splicing onl...
Citation: Algorithms for Molecular Biology 2006 1:14
Discovering approximately repeated patterns, or motifs, in biological sequences is an important and widely-studied problem in computational molecular biology. Most frequently, motif finding applications arise ...
Citation: Algorithms for Molecular Biology 2006 1:13
The String Barcoding (SBC) problem, introduced by Rash and Gusfield (RECOMB, 2002), consists in finding a minimum set of substrings that can be used to distinguish between all members of a set of given strings...
Citation: Algorithms for Molecular Biology 2006 1:12
Bifurcation analysis has proven to be a powerful method for understanding the qualitative behavior of gene regulatory networks. In addition to the more traditional forward problem of determining the mapping from ...
Citation: Algorithms for Molecular Biology 2006 1:11
Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both problems can be addressed by m...
Citation: Algorithms for Molecular Biology 2006 1:10
Given a set S of n locally aligned sequences, it is a needed prerequisite to partition it into groups of very similar sequences to facilitate subsequent computations, such as the generation of a phylogenetic tree...
Citation: Algorithms for Molecular Biology 2006 1:9
Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcri...
Citation: Algorithms for Molecular Biology 2006 1:8
Most cellular processes are carried out by multi-protein complexes, groups of proteins that bind together to perform a specific task. Some proteins form stable complexes, while other proteins form transient as...
Citation: Algorithms for Molecular Biology 2006 1:7
Automated software tools for multiple alignment often fail to produce biologically meaningful results. In such situations, expert knowledge can help to improve the quality of alignments.
Citation: Algorithms for Molecular Biology 2006 1:6
The technique of Finite Markov Chain Imbedding (FMCI) is a classical approach to complex combinatorial problems related to sequences. In order to get efficient algorithms, it is known that such approaches need...
Citation: Algorithms for Molecular Biology 2006 1:5
Motif patterns of maximal saturation emerged originally in contexts of pattern discovery in biomolecular sequences and have recently proven a valuable notion also in the design of data compression schemes. Inf...
Citation: Algorithms for Molecular Biology 2006 1:4
RNA has been recognized as a key player in cellular regulation in recent years. In many cases, non-coding RNAs exert their function by binding to other nucleic acids, as in the case of microRNAs and snoRNAs. T...
Citation: Algorithms for Molecular Biology 2006 1:3
The genomes of many species are dominated by short sequences repeated consecutively. It is estimated that over 10% of the human genome consists of tandemly repeated sequences. Finding repeated regions in long ...
Citation: Algorithms for Molecular Biology 2006 1:2
This editorial announces Algorithms for Molecular Biology, a new online open access journal published by BioMed Central. By launching the first open access journal on algorithmic bioinformatics, we provide a foru...
Citation: Algorithms for Molecular Biology 2006 1:1
Algorithms for Molecular Biology