bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterizing proteolytic cleavage site activity using bio-basis function neural networks
Authors: Thomson Rebecca , Hodgman T. Charles , Yang Zheng Rong , Doyle Austin K. 
Published: September 2003

Abstract
Motivation: In protein chemistry, proteomics and biopharmaceutical development, there is a desire to know not only where a protein is cleaved by a protease, but also the susceptibility of its cleavage sites. The current tools for proteolytic cleavage prediction have often relied purely on regular expressions, or involve models that do not represent biological data well.
Results: A novel methodology for characterizing proteolytic cleavage site activities has been developed, which incorporates two fundamental features: activity class prediction and the use of an amino acid similarity matrix for (non-parametric) neural learning. The first solved the problem of predicting proteolytic efficiency. The second significantly improved the robustness in prediction and reduced the time complexity for learning. This study shows that activity class prediction is successful when applying this methodology to the prediction and characterization of Trypsin cleavage sites and the prediction of HIV protease cleavage sites.
Availability: Requests for software and data should be made respectively to Dr Zheng Rong Yang and Miss Rebecca Thomson.
New algorithms for multi-class cancer diagnosis using tumor gene expression signatures
Authors: Bagirov A. M. , Ferguson B. , Ivkovic S. , Saunders G. , Yearwood J. 
Published: September 2003

Abstract
Motivation: The increasing use of DNA microarray-based tumor gene expression profiles for cancer diagnosis requires mathematical methods with high accuracy for solving clustering, feature selection and classification problems of gene expression data.
Results: New algorithms are developed for solving clustering, feature selection and classification problems of gene expression data. The clustering algorithm is based on optimization techniques and allows the calculation of clusters step-by-step. This approach allows us to find as many clusters as a data set contains with respect to some tolerance. Feature selection is crucial for a gene expression database. Our feature selection algorithm is based on calculating overlaps of different genes. The database used, contains over 16 000 genes and this number is considerably reduced by feature selection. We propose a classification algorithm where each tissue sample is considered as the center of a cluster which is a ball. The results of numerical experiments confirm that the classification algorithm in combination with the feature selection algorithm perform slightly better than the published results for multi-class classifiers based on support vector machines for this data set.
Availability: Available on request from the authors.
Haplotype inference by maximum parsimony
Authors: Wang Lusheng , Xu Ying 
Published: September 2003

Abstract
Motivation: Haplotypes have been attracting increasing attention because of their importance in analysis of many fine-scale molecular-genetics data. Since direct sequencing of haplotype via experimental methods is both time-consuming and expensive, haplotype inference methods that infer haplotypes based on genotype samples become attractive alternatives.
Results: (1) We design and implement an algorithm for an important computational model of haplotype inference that has been suggested before in several places. The model finds a set of minimum number of haplotypes that explains the genotype samples. (2) Strong supports of this computational model are given based on the computational results on both real data and simulation data. (3) We also did some comparative study to show the strength and weakness of this computational model using our program.
Availability: The software HAPAR is free for non-commercial uses. Available upon request (lwang@cs.cityu.edu.hk).
Recognizing the fold of a protein structure
Authors: Harrison Andrew , Pearl Frances , Sillitoe Ian , Slidel Tim , Mott Richard , Thornton Janet , Orengo Christine 
Published: September 2003

Abstract
This paper reports a graph-theoretic program, GRATH, that rapidly, and accurately, matches a novel structure against a library of domain structures to find the most similar ones. GRATH generates distributions of scores by comparing the novel domain against the different types of folds that have been classified previously in the CATH database of structural domains.
GRATH uses a measure of similarity that details the geometric information, number of secondary structures and number of residues within secondary structures, that any two protein structures share. Although GRATH builds on well established approaches for secondary structure comparison, a novel scoring scheme has been introduced to allow ranking of any matches identified by the algorithm. More importantly, we have benchmarked the algorithm using a large dataset of 1702 non-redundant structures from the CATH database which have already been classified into fold groups, with manual validation. This has facilitated introduction of further constraints, optimization of parameters and identification of reliable thresholds for fold identification. Following these benchmarking trials, the correct fold can be identified with the top score with a frequency of 90%. It is identified within the ten most likely assignments with a frequency of 98%.
GRATH has been implemented to use via a server (http://www.biochem.ucl.ac.uk/cgi-bin/cath/Grath.pl). GRATH's speed and accuracy means that it can be used as a reliable front-end filter for the more accurate, but computationally expensive, residue based structure comparison algorithm SSAP, currently used to classify domain structures in the CATH database. With an increasing number of structures being solved by the structural genomics initiatives, the GRATH server also provides an essential resource for determining whether newly determined structures are related to any known structures from which functional properties may be inferred.
MutDB: annotating human variation with functionally relevant data
Authors: Mooney Sean D. , Altman Russ B. 
Published: September 2003

Abstract
Summary: We have developed a resource, MutDB (http://mutdb.org/), to aid in determining which single nucleotide polymorphisms (SNPs) are likely to alter the function of their associated protein product. MutDB contains protein structure annotations and comparative genomic annotations for 8000 disease-associated mutations and SNPs found in the UCSC Annotated Genome and the human RefSeq gene set. MutDB provides interactive mutation maps at the gene and protein levels, and allows for ranking of their predicted functional consequences based on conservation in multiple sequence alignments.
Availability: http://mutdb.org/
Supplementary information: http://mutdb.org/about/about.html
Controlling false-negative errors in microarray differential expression analysis: a PRIM approach
Authors: Cole Steve W. , Galic Zoran , Zack Jerome A. 
Published: September 2003

Abstract
Motivation: Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed ‘false negative’ error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements.
Results: Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays.
Availability: Freestanding JAVA application at http://microarray.crump.ucla.edu/focus
Protein Ligand Database (PLD): additional understanding of the nature and specificity of protein–ligand complexes
Authors: Puvanendrampillai Dushyanthan , Mitchell John B. O. 
Published: September 2003

Abstract
Summary: The Protein Ligand Database (PLD) is a publicly available web-based database that aims to provide further understanding of protein–ligand interactions. The PLD contains biomolecular data including calculated binding energies, Tanimoto ligand similarity scores and protein percentage sequence similarities. The database has potential for application as a tool in molecular design.
Availability: http://www-mitchell.ch.cam.ac.uk/pld/
Soap-HT-BLAST: high throughput BLAST based on Web services
Authors: Wang Jiren , Mu Qing 
Published: September 2003

Abstract
Summary: A high throughput Basic Local Alignment Search Tool (BLAST) system based on Web services is implemented. It provides an alternative BLAST service and allows users to perform multiple BLAST queries at one run in a distributed, parallel environment through the Internet.
Availability: It is available at http://mammoth.bii.a-star.edu.sg/webservices/htblast/index.html and at http://www.bii.a-star.edu.sg/jiren/download.html
Transformation and normalization of oligonucleotide microarray data
Authors: Geller Sue C. , Gregg Jeff P. , Hagerman Paul , Rocke David M. 
Published: September 2003

Abstract
Motivation: Most methods of analyzing microarray data or doing power calculations have an underlying assumption of constant variance across all levels of gene expression. The most common transformation, the logarithm, results in data that have constant variance at high levels but not at low levels. Rocke and Durbin showed that data from spotted arrays fit a two-component model and Durbin, Hardin, Hawkins, and Rocke, Huber et al. and Munson provided a transformation that stabilizes the variance as well as symmetrizes and normalizes the error structure. We wish to evaluate the applicability of this transformation to the error structure of GeneChip microarrays.
Results: We demonstrate in an example study a simple way to use the two-component model of Rocke and Durbin and the data transformation of Durbin, Hardin, Hawkins and Rocke, Huber et al. and Munson on Affymetrix GeneChip data. In addition we provide a method for normalization of Affymetrix GeneChips simultaneous with the determination of the transformation, producing a data set without chip or slide effects but with constant variance and with symmetric errors. This transformation/normalization process can be thought of as a machine calibration in that it requires a few biologically constant replicates of one sample to determine the constant needed to specify the transformation and normalize. It is hypothesized that this constant needs to be found only once for a given technology in a lab, perhaps with periodic updates. It does not require extensive replication in each study. Furthermore, the variance of the transformed pilot data can be used to do power calculations using standard power analysis programs.
Availability: SPLUS code for the transformation/normalization for four replicates is available from the first author upon request. A program written in C is available from the last author.
An XML message broker framework for exchange and integration of microarray data
Authors: Tjandra Donny , Wong Stephen , Shen Weimin , Pulliam Brian , Yu Elaine , Esserman Laura 
Published: September 2003

Abstract
Motivation: Microarrays are an important research tool for the advancement of basic biological sciences. However this technology has yet to be integrated with clinical decision making. We have implemented an information framework based on the Microarray Gene Expression Markup Language (MAGE-ML) specification. We are using this framework to develop a test-bed integrated database application to identify genomic and imaging markers for diagnosis of breast cancer.
Results: We developed extensible software architecture for retrieving data from different microarray databases using MAGE-ML and for combining microarray data with breast cancer image analysis and clinical data for correlation studies. The framework we developed will provide the necessary data integration to move microarray research from basic biological sciences to clinical applications.
Availability: Open source software will be available from SourceForge (http://sourceforge.net/projects/microsoap/).
Examining the independent binding assumption for binding of peptide epitopes to MHC-I molecules
Authors: Peters Björn , Tong Weiwei , Sidney John , Sette Alessandro , Weng Zhiping 
Published: September 2003

Abstract
Motivation: Various methods have been proposed to predict the binding affinities of peptides to Major Histocompatibility Complex class I (MHC-I) molecules based on experimental binding data. They can be classified into two groups: (1) AIB methods that assume independent contributions of all peptide positions to the binding to MHC-I molecule (e.g. scoring matrices) and (2) general methods which can take into account interactions between different positions (e.g. artificial neural networks). We aim to compare the prediction accuracies of these methods, and quantify the impact of interactions between peptide positions.
Results: We compared several previously published and widely used methods and discovered that the best AIB methods gave significantly better predictions than three previously published general methods, possibly due to the lack of a sufficient training data for the general methods. The best results, however, were achieved with our newly developed general method, which combined a matrix describing independent binding with pair coefficients describing pair-wise interactions between peptide positions. The pair coefficients consistently but only slightly improved prediction accuracy, and were much smaller than the matrix entries. This explains why neglecting them—as is done in AIB methods—can still lead to good predictions.
Availability: The new prediction model is implemented at http://zlab.bu.edu/SMM. The underlying matrix and pair coefficients are also available as supplementary materials.
The EMBL sequence version archive
Authors: Leinonen Rasko , Nardone Francesco , Oyewole Olalekan , Redaschi Nicole , Stoehr Peter 
Published: September 2003

Abstract
Summary: The EMBL Nucleotide Sequence Database, maintained at the European Bioinformatics institute, is Europe's primary nucleotide sequences database. Its entries are subject to changes, but only the most recent versions are preserved in the database. The EMBL Sequence Version Archive is a new publicly available database retaining also the earlier versions of these entries.
Availability: http://www.ebi.ac.uk/embl/sva/
RVP-net: online prediction of real valued accessible surface area of proteins from single sequences
Authors: Ahmad Shandar , Gromiha M. Michael , Sarai Akinori 
Published: September 2003

Abstract
Summary: RVP-net is an online program for the prediction of real valued solvent accessibility. All previous methods of accessible surface area (ASA) predictions classify amino acid residues into exposure states and named them buried or exposed based on different thresholds. Real values in some cases were generated by taking the mid points of these state thresholds. This is the first method, which provides a direct prediction of ASA without making exposure categories and achieves results better than 19% mean absolute error. To facilitate batch processing of several sequences, a standalone version of this tool is also provided.
Availability: Online predictions are available at http://www.netasa.org/rvp-net/. Standalone version of the program can be obtained from the corresponding author by E-mail request.
Parallel BLAST on split databases
Authors: Mathog David R. 
Published: September 2003

Abstract
Summary: BLAST programs often run on large SMP machines where multiple threads can work simultaneously and there is enough memory to cache the databases between program runs. A group of programs is described which allows comparable performance to be achieved with a Beowulf configuration in which no node has enough memory to cache a database but the cluster as an aggregate does. To achieve this result, databases are split into equal sized pieces and stored locally on each node. Each query is run on all nodes in parallel and the resultant BLAST output files from all nodes merged to yield the final output.
Availability: Source code is available from ftp://saf.bio.caltech.edu/
The design of Jemboss: a graphical user interface to EMBOSS
Authors: Carver Tim , Bleasby Alan 
Published: September 2003

Abstract
Design: Jemboss is a graphical user interface (GUI) for the European Molecular Biology Open Software Suite (EMBOSS). It is being developed at the MRC UK HGMP-RC as part of the EMBOSS project. This paper explains the technical aspects of the Jemboss client–server design. The client–server model optionally allows that a Jemboss user have an account on the remote server. The Jemboss client is written in Java and is downloaded automatically to a user's workstation via Java Web Start using the HTML protocol. The client then communicates with the remote server using SOAP (Simple Object Access Protocol). A Tomcat server listens on the remote machine and communicates the SOAP requests to a Jemboss server, again written in Java. This Java server interprets the client requests and executes them through Java Native Interface (JNI) code written in the C language. Another C program having setuid privilege, jembossctl, is called by the JNI code to perform the client requests under the user's account on the server. The commands include execution of EMBOSS applications, file management and project management tasks. Jemboss allows the use of JSSE for encryption of communication between the client and server. The GUI parses the EMBOSS Ajax Command Definition language for form generation and maximum input flexibility. Jemboss interacts directly with the EMBOSS libraries to allow dynamic generation of application default settings.
Results: This interface is part of the EMBOSS distribution and has attracted much interest. It has been set up at many other sites globally as well as being used at the HGMP-RC for registered users.
Availability: The software, EMBOSS and Jemboss, is freely available to academics and commercial users under the GPL licence. It can be downloaded from the EMBOSS ftp server: http://www.uk.embnet.org/Software/EMBOSS/, ftp://ftp.uk.embnet.org/pub/EMBOSS/. Registered HGMP-RC users can access an installed server from: http://www.uk.embnet.org/Software/EMBOSS/Jemboss/
Identification and quantification of disease-related gene clusters
Authors: Firneisz Gábor , Zehavi Idit , Vermes Csaba , Hanyecz Anita , Frieman Joshua A. , Glant Tibor T. 
Published: September 2003

Abstract
Motivation: DNA microarray technology and the completion of human and mouse genome sequencing programs are now offering new avenues for the investigation of complex genetic diseases. In particular, this makes possible the study of the spatial distribution of disease-related genes within the genome. We report on the first systematic search for clustering of genes associated with a polygenic autoimmune disease.
Results: Using a set of cDNA microarray chip experiments in two mouse models of rheumatoid arthritis, we have identified ∼200 genes based on their expression in inflamed joints and mapped them into the genome. We compute the spatial autocorrelation function of the selected genes and find that they tend to cluster over scales of a few megabase pairs. We then identify significant gene clusters using a friends-of-friends algorithm. This approach should aid in discovering functionally related gene clusters in the mammalian genome.
A tool-kit for cDNA microarray and promoter analysis
Authors: Shah N. H. , King D. C. , Shah P. N. , Fedoroff N. V. 
Published: September 2003

Abstract
We describe two sets of programs for expediting routine tasks in analysis of cDNA microarray data and promoter sequences. The first set permits bad data points to be flagged with respect to a number of parameters and performs normalization in three different ways. It allows combining of result files into comprehensive data sets, evaluation of the quality of both technical and biological replicates and row and/or column standardization of data matrices. The second set supports mapping ESTs in the genome, identifying the corresponding genes and recovering their promoters, analyzing promoters for transcription factor binding sites, and visual representation of the results. The programs are designed primarily for Arabidopsis thaliana researchers, but can be adapted readily for other model systems.
Availability and Supplementary information: http://www.personal.psu.edu/nhs109/Programs/
Automatic registration of microarray images. I. Rectangular grid
Authors: Galinsky Vitaly L. 
Published: September 2003

Abstract
Motivation: The analysis of high-throughput experiment data provided by microarrays becomes increasingly more and more important part of modern biological science. Microarrays allow to conduct genotyping or gene expression experiments on hundreds of thousands of test genes in parallel. Because of the large and constantly growing amount of experimental data the necessity of efficiency, robustness and complete automation of microarray image analysis algorithms is gaining significant attention in the field of microarray processing.
Results: The author presents here an efficient and completely automatic image registration algorithm (that is an algorithm for spots and blocks indexing) that allows to process a wide variety of microarray slides with different parameters of grid and block spacing as well as spot sizes. The algorithm scales linearly with the grid size, the time complexity is O(M), where M is number of rows × number of columns. It can successfully cope with local and global distortions of the grid, such as focal distortions and non-orthogonal transformations. The algorithm has been tested both on CCD and scanned images and showed very good performance—the processing time of a single slide with 44 blocks of 200 × 200 grid points (or 1 760 000 grid points total) was about 10 s.
Availability: The test implementation of the algorithm will be available upon request for academics.
Supplementary information: http://fleece.ucsd.edu/~vit/Registration_Supplement.pdf