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PubMed2006

Recrafting the neighbor-joining method.

BACKGROUND: The neighbor-joining method by Saitou and Nei is a widely used method for constructing phylogenetic trees. The formulation of the method gives rise to a canonical Theta(n3) algorithm upon which all existing implementations are based. RESULTS: In this paper we present techniques for speeding up the canonical neighbor-joining method. Our algorithms construct the same phylogenetic trees as the canonical neighbor-joining method. The best-case running time of our algorithms are O(n2) but the worst-case remains O(n3). We empirically evaluate the performance of our algoritms on distance matrices obtained from the Pfam collection of alignments. The experiments indicate that the running time of our algorithms evolve as Theta(n2) on the examined instance collection. We also compare the running time with that of the QuickTree tool, a widely used efficient implementation of the canonical neighbor-joining method. CONCLUSION: The experiments show that our algorithms also yield a significant speed-up, already for medium sized instances.

Algorithms↗

PubMed2006

ROKU: a novel method for identification of tissue-specific genes.

BACKGROUND: One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. RESULTS: We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. CONCLUSION: ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes.

Algorithms↗

PubMed2005

Exploration of phylogenetic data using a global sequence analysis method.

BACKGROUND: Molecular phylogenetic methods are based on alignments of nucleic or peptidic sequences. The tremendous increase in molecular data permits phylogenetic analyses of very long sequences and of many species, but also requires methods to help manage large datasets. RESULTS: Here we explore the phylogenetic signal present in molecular data by genomic signatures, defined as the set of frequencies of short oligonucleotides present in DNA sequences. Although violating many of the standard assumptions of traditional phylogenetic analyses--in particular explicit statements of homology inherent in character matrices--the use of the signature does permit the analysis of very long sequences, even those that are unalignable, and is therefore most useful in cases where alignment is questionable. We compare the results obtained by traditional phylogenetic methods to those inferred by the signature method for two genes: RAG1, which is easily alignable, and 18S RNA, where alignments are often ambiguous for some regions. We also apply this method to a multigene data set of 33 genes for 9 bacteria and one archea species as well as to the whole genome of a set of 16 gamma-proteobacteria. In addition to delivering phylogenetic results comparable to traditional methods, the comparison of signatures for the sequences involved in the bacterial example identified putative candidates for horizontal gene transfers. CONCLUSION: The signature method is therefore a fast tool for exploring phylogenetic data, providing not only a pretreatment for discovering new sequence relationships, but also for identifying cases of sequence evolution that could confound traditional phylogenetic analysis.

Algorithms↗

PubMed1992

Elevated growth hormone secretory rate in premature infants: deconvolution analysis of pulsatile growth hormone secretion in the neonate.

Premature infants have higher circulating concentrations of growth hormone (GH) than term infants. Previous investigations of these differences have used sampling frequencies of every 30 min with subsequent application of pulse detection algorithms, such as the CLUSTER program, to assess serum GH pulse parameters. To determine differences in GH secretory rates or GH t1/2 values between premature and term infants, we have sampled 11 neonates at 15-min intervals. We performed deconvolution analysis of the resultant plasma GH values to estimate GH secretory and clearance parameters. Five premature infants (gestational age range 24-34 wk) and six term infants (gestational age range 38-42 wk) were sampled every 15 min for 6 h. All subjects had indwelling arterial catheters. GH was measured (in duplicate) by RIA using 10 microL of plasma. Premature infants had higher secretory burst amplitudes (2.2 +/- 0.13 micrograms/L/min versus 1.4 +/- 0.27 micrograms/L/min, p = 0.02), higher production rates (product of the total number of bursts and the mean mass of GH secreted per burst, 811 +/- 173 micrograms/L/6 h versus 283 +/- 77 micrograms/L/6 h, p = 0.03), and a higher mass of GH per secretory burst (106 +/- 25 micrograms/L versus 38 +/- 11 micrograms/L, p = 0.049) than term infants. The integrated plasma GH concentration exhibited a strong trend toward a higher value in the premature infants (18,100 +/- 800 micrograms/L versus 10,200 +/- 2,700 micrograms/L, p = 0.067).(ABSTRACT TRUNCATED AT 250 WORDS)

Female↗

PubMed2004

Cell-based partitioning.

Partitioning techniques are widely used to classify compound sets or databases according to specific chemical or biological criteria. Partitioning is conceptually related to, yet algorithmically distinct from, conventional clustering methods and is particularly suitable for efficient processing of very large compound sets. Currently, some of the most popular partitioning approaches in the chemoinformatics field involve dimension reduction of initially defined chemistry spaces and creation of subsections of low-dimensional space for molecular classification. These subsections are often called cells. Original chemical reference spaces are generated through selection of various descriptors of molecular structure and properties. Principles and methodological aspects of dimension reduction of chemical spaces and compound partitioning in low-dimensional space are described herein.

Information Services↗

PubMed2005

Analysis of microarray experiments for pulmonary fibrosis.

Microarray technology allows the investigator to examine the simultaneous expression of thousands of genes in a given cell or tissue. Such experiments that probe tens of thousands of genes produce immense amounts of information. In recent years, there has been a steady increase in the availability of tools for analysis of microarray data. Although many commercial tools are being aggressively marketed, we mostly use shareware tools. In this chapter, we present our approach to the analysis of microarray data mainly using tools that were generated by our collaborators or that are freely available. Step-by-step explanations of software operation are provided.

Algorithms↗

PubMed2006

Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Algorithms↗

PubMed2005

Exploring the helix-coil transition via all-atom equilibrium ensemble simulations.

The ensemble folding of two 21-residue alpha-helical peptides has been studied using all-atom simulations under several variants of the AMBER potential in explicit solvent using a global distributed computing network. Our extensive sampling, orders of magnitude greater than the experimental folding time, results in complete convergence to ensemble equilibrium. This allows for a quantitative assessment of these potentials, including a new variant of the AMBER-99 force field, denoted AMBER-99 phi, which shows improved agreement with experimental kinetic and thermodynamic measurements. From bulk analysis of the simulated AMBER-99 phi equilibrium, we find that the folding landscape is pseudo-two-state, with complexity arising from the broad, shallow character of the "native" and "unfolded" regions of the phase space. Each of these macrostates allows for configurational diffusion among a diverse ensemble of conformational microstates with greatly varying helical content and molecular size. Indeed, the observed structural dynamics are better represented as a conformational diffusion than as a simple exponential process, and equilibrium transition rates spanning several orders of magnitude are reported. After multiple nucleation steps, on average, helix formation proceeds via a kinetic "alignment" phase in which two or more short, low-entropy helical segments form a more ideal, single-helix structure.

Algorithms↗

PubMed2005

An information theoretic approach to macromolecular modeling: I. Sequence alignments.

We are interested in applying the principles of information theory to structural biology calculations. In this article, we explore the information content of an important computational procedure: sequence alignment. Using a reference state developed from exhaustive sequences, we measure alignment statistics and evaluate gap penalties based on first-principle considerations and gap distributions. We show that there are different gap penalties for different alphabet sizes and that the gap penalties can depend on the length of the sequences being aligned. In a companion article, we examine the information content of molecular force fields.

Algorithms↗

PubMed1994

Secretion pattern of immunoreactive inhibin in men.

Chronological changes in serum concentrations of inhibin, a gonadal glycoprotein hormone, were studied in healthy male volunteers (age 24-27 years). Secretion profiles of immunoreactive inhibin (ir-inhibin) were compared with those of luteinizing hormone (LH), follicle-stimulating hormone (FSH) and testosterone. Blood samples were collected every 15 min for 24 h. Serum inhibin concentrations were measured by a two-site immunoenzymatic assay with antibodies raised against distinct epitopes of the recombinant 1-32 amino acids of the alpha-subunit of human inhibin. The normal range for men was 0.79-3.1 U/l x 10(-3), the sensitivity of the assay was 0.1 U/l x 10(-3) (cv: within-assay, 6.8%; between-assay, 8.2%). Luteinizing hormone and FSH were measured by immunoradiometric assay and testosterone by radioimmunoassay. Secretion profiles of inhibin and testosterone were tested for diurnal variations by cosinor rhythmometry. Highest ir-inhibin concentrations were observed in the morning at 08.00 h, with peak values of 2.45-3.20 U/l x 10(-3). During the evening and the night, ir-inhibin levels were relatively low; lowest concentrations were observed between 01.00 h and 02.00 h at night: 1.20-1.86 U/l x 10(-3). Highest testosterone levels were observed in the morning (20.5-36.6 pmol/l), lowest concentrations were detected at night (7.35-12.6 pmol/l). Cosinor rhythmometry supported the suggestion that there is a clear circadian secretion of ir-inhibin and testosterone, respectively. The secretion pattern of ir-inhibin was analyzed by the Cluster pulse analysis computed algorithm, which identified four to seven inhibin pulses per day, depending on the person under observation.2+ volunteers follow a clear diurnal rhythm.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed2006

Resources and tools for investigating biomolecular networks in mammals.

Molecular databases serve as primary information resources for the analysis of biological networks providing an essential and invaluable treasure for information exploration. Tools for projecting experimental data sets onto known functional information are a major need to support the analysis of samples produced in clinical research. A new concept is the notation of functional modules, i.e. the characterisation of sets of proteins that perform a defined biological function in cooperation. The determination and analysis of functional modules overcome the limitations of the analysis of individual genes and their properties. Although functional modules are not suitable to fully capture systems properties, they have the potential to unify the information generated by different types of experiments. We describe advances related to the problem of integrating heterogeneous data sets into functional modules for mouse and/or human cellular networks based on publicly available data resources, including advances in the design of ontologies for functional classification, problems of automatic protein functional annotation and integration of microarray data.

Algorithms↗

PubMed2002

[A comparison between physicians' interpretation and a CAD system's cancer detection by using a mammogram database in a physicians' self-learning course].

We have been developing automated detection algorithms for masses and clustered microcalcifications in a mammography computer-aided diagnosis (CAD) system. In this study, we investigated the potential of our CAD system by comparing 579 physicians' interpretation results with that of the CAD system's cancer detection for 100 mammograms (21 malignant and 29 benign cases) employed in a physicians' self-learning course. As a result, our CAD system detected 7 out of 8 malignant lesions whose physicians' averaged sensitivity was less than 60%. Although the average of physicians' sensitivities were 76% (about 16 cases), the CAD system's detection rate was 90% (19 cases). Sensitivity was raised up to 97% if the physicians' interpretation and the CAD system's detection result were treated in a matter of logical OR. Thus, it was raised the possibility that even the less-experienced physicians would diagnose with a higher sensitivity by using the computer output as a guide effectively.

Breast Neoplasms↗

PubMed2001

Analysis of patient flows via data mining.

The paper presents DoMiner, a data mining tool for the analysis of patient flows among public hospitals and care units. DoMiner is based on the theory of rough sets, and allows for the extraction of association rules from data base tables. The paper describes both the clustering and rule extraction algorithm of DoMiner, and illustrates an introductory analysis example.

Algorithms↗

PubMed2003

Microarray-based cancer diagnosis with artificial neural networks.

In recent years, the advent of experimental methods to probe gene expression profiles of cancer on a genome-wide scale has led to widespread use of supervised machine learning algorithms to characterize these profiles. The main applications of these analysis methods range from assigning functional classes of previously uncharacterized genes to classification and prediction of different cancer tissues. This article surveys the application of machine learning algorithms to classification and diagnosis of cancer based on expression profiles. To exemplify the important issues of the classification procedure, the emphasis of this article is on one such method, namely artificial neural networks. In addition, methods to extract genes that are important for the performance of a classifier, as well as the influence of sample selection on prediction results are discussed.

Algorithms↗

PubMed2003

Profiling of genes differentially expressed between fetal liver and postnatal liver using high-density oligonucleotide DNA array.

The liver is an essential organ in humans not only for the production and storage of energy but also for detoxification of chemical compounds, but knowledge about changes in the gene expression profile in the human liver during the prenatal and postnatal periods is limited. Profiling of genes differentially expressed between the fetal liver (FL) and the postnatal liver (PNL) is one of the methods to investigate candidates affecting the difference in biological characteristics between FL and PNL. To identify genes differentially expressed between FL and PNL (childhood and adult liver), we analyzed the gene expression profiles across 9 FL and 14 PNL samples using a high-density oligonucleotide DNA array. Using Mann-Whitney U test followed by k-nearest-neighbors (supervised learning method) and hierarchical clustering (unsupervised learning method) algorithms, we found 33 genes clearly discriminating between the FL group and PNL group. The functional classification of the 33 genes identified was related to several kinds of biological pathways, regulating the cell cycle (PCNA, CDC7L1, CCND3, YWHA1, PKMYT1), DNA replication and repair (RFC4, RECQ2, PCNA, NAP1L1), cell growth (IGF2, IGFBP2, PRSS11), hormonal signals (AR, SRD5A1, NR1I3), and cellular metabolism (E2-EPF, WWP1, CYP2C9, CYP2E1, CYP2A6, CYP2A7, CYP2A13, CYP4F2, CYP3A4, DDT). The results presented herein provide evidence of a differential expression profile of genes regulating the cell cycle, DNA replication and repair, cell growth, regulation of hormonal signals, and cellular metabolism, between FL and PNL in humans. The 33 genes identified in this study are suggested to be useful markers clearly discriminating between FL and PNL using the gene expression profile.

Adult↗

PubMed2004

Establishment of the methods for searching eukaryotic gene cis-regulatory modules.

On the basis of the knowledge of eukaryotic gene regulation, we modified the method in three aspects: (1) Searching the cis-regulatory modules (CRM) according Fasta or Blast sequence with multiple sequence and low E value, followed by mutual scoring of these sequence with Smith-Waterman algorithms and finally by clustering analysis; (2) Searching the transcription factor-binding site using International Union of Pure and Applied Chemistry, Position-Weight Matrix(PWM) and Dyed method; (3) Designing and implementation of data analysis based on the software in Windows 2000 and UNIX using object-oriented technology. The results of analysis of the major histocompatibility complex gene family show that this procedure may accurately locate the regions that contain some of the CRMs.

Computational Biology↗

PubMed2006

A fully resolved consensus between fully resolved phylogenetic trees.

Nowadays, there are many phylogeny reconstruction methods, each with advantages and disadvantages. We explored the advantages of each method, putting together the common parts of trees constructed by several methods, by means of a consensus computation. A number of phylogenetic consensus methods are already known. Unfortunately, there is also a taboo concerning consensus methods, because most biologists see them mainly as comparators and not as phylogenetic tree constructors. We challenged this taboo by defining a consensus method that builds a fully resolved phylogenetic tree based on the most common parts of fully resolved trees in a given collection. We also generated results showing that this consensus is in a way a kind of "median" of the input trees; as such it can be closer to the correct tree in many situations.

Algorithms↗

PubMed2005

CiteSpace II: visualization and knowledge discovery in bibliographic databases.

This article presents a description and case study of CiteSpace II, a Java application which supports visual exploration with knowledge discovery in bibliographic databases. Highly cited and pivotal documents, areas of specialization within a knowledge domain, and emergence of research topics are visually mapped through a progressive knowledge domain visualization approach to detecting and visualizing trends and patterns in scientific literature. The test case in this study is progressive knowledge domain visualization of the field of medical informatics. Datasets based on publications from twelve journals in the medical informatics field covering the time period from 1964-2004 were extracted from PubMed and Web of Science (WOS) and developed as testbeds for evaluation of the CiteSpace system. Two resulting document-term co-citation and MeSH term co-occurrence visualizations are qualitatively evaluated for identification of pivotal documents, areas of specialization, and research trends. Practical applications in bio-medical research settings are discussed.

Algorithms↗