Hierarchical Access System for Sequence Libraries in Europe (HASSLE): a tool to access sequence databases remotely

Sequence databases in biology are growing exponentially. Not only are large sites needed to keep the data, but the number of customers is continuously increasing. Network access plays a key role in utilizing remote resources. However, both synchronous and asynchronous access require tools that are currently non-standard in molecular biology computing. Additionally, information discovery of today frequently focuses on centers rather a hierarchically interconnected facilities. HASSLE (Hierarchical Access System for Sequence Libraries in Europe) is an implementation of an application-independent, user-transparent access tool in molecular biology. It features tools for both clients and information providers to permit accounting and/or prioritization on various levels. HASSLE focuses on the network aspect of the molecular biology computing and assumes that it is possible to have database applications as remote ‘services' (programs, program packages or utilities) which can be started by a simple command script after a suitable feed of datafiles. The current system provides these services for searching with programs like FASTA or BLAST which are compiled as obtained from vendors or server

A compression mechanism for sequence databases to improve the efficiency of conventional tools

This paper describes a method to compress molecular biology databases that are characterized by an increasing proportion of data derived from genome projects. The performance of our tool has been tested on various data files of the EMBL nucleotide sequence database. The best compression ratios were achieved on EST (Expressed Sequence Tags) data, typically derived from large-scale sequence projects. The compression of sequence database updates was tested in combination with the common Unix compression program ‘compress'. Our tool improved the efficiency of ‘compress' on average by 16

Computational verification of published human mutations

Magister Scientiae - MScThe completion of the Human Genome Project, a remarkable feat by any measure, has provided over three billion bases of reference nucleotides for comparative studies. The next, and perhaps more challenging step is to analyse sequence variation and relate this information to important phenotypes. Most human sequence variations are characterized by structural complexity and, are hence, associated with abnormal functional dynamics. This thesis covers the assembly of a computational platform for verifying these variations, based on accurate, published, experimental data.South Afric

HAPPI-2: a Comprehensive and High-quality Map of Human Annotated and Predicted Protein Interactions

BACKGROUND: Human protein-protein interaction (PPI) data is essential to network and systems biology studies. PPI data can help biochemists hypothesize how proteins form complexes by binding to each other, how extracellular signals propagate through post-translational modification of de-activated signaling molecules, and how chemical reactions are coupled by enzymes involved in a complex biological process. Our capability to develop good public database resources for human PPI data has a direct impact on the quality of future research on genome biology and medicine. RESULTS: The database of Human Annotated and Predicted Protein Interactions (HAPPI) version 2.0 is a major update to the original HAPPI 1.0 database. It contains 2,922,202 unique protein-protein interactions (PPI) linked by 23,060 human proteins, making it the most comprehensive database covering human PPI data today. These PPIs contain both physical/direct interactions and high-quality functional/indirect interactions. Compared with the HAPPI 1.0 database release, HAPPI database version 2.0 (HAPPI-2) represents a 485% of human PPI data coverage increase and a 73% protein coverage increase. The revamped HAPPI web portal provides users with a friendly search, curation, and data retrieval interface, allowing them to retrieve human PPIs and available annotation information on the interaction type, interaction quality, interacting partner drug targeting data, and disease information. The updated HAPPI-2 can be freely accessed by Academic users at http://discovery.informatics.uab.edu/HAPPI . CONCLUSIONS: While the underlying data for HAPPI-2 are integrated from a diverse data sources, the new HAPPI-2 release represents a good balance between data coverage and data quality of human PPIs, making it ideally suited for network biology

Pharmacodynamics miner : an automated extraction of pharmacodynamic drug interactions

Indiana University-Purdue University Indianapolis (IUPUI)Pharmacodynamics (PD) studies the relationship between drug concentration and drug effect on target sites. This field has recently gained attention as studies involving PD Drug-Drug interactions (DDI) assure discovery of multi-targeted drug agents and novel efficacious drug combinations. A PD drug combination could be synergistic, additive or antagonistic depending upon the summed effect of the drug combination at a target site. The PD literature has grown immensely and most of its knowledge is dispersed across different scientific journals, thus the manual identification of PD DDI is a challenge. In order to support an automated means to extract PD DDI, we propose Pharmacodynamics Miner (PD-Miner). PD-Miner is a text-mining tool, which is capable of identifying PD DDI from in vitro PD experiments. It is powered by two major features, i.e., collection of full text articles and in vitro PD ontology. The in vitro PD ontology currently has four classes and more than hundred subclasses; based on these classes and subclasses the full text corpus is annotated. The annotated full text corpus forms a database of articles, which can be queried based upon drug keywords and ontology subclasses. Since the ontology covers term and concept meanings, the system is capable of formulating semantic queries. PD-Miner extracts in vitro PD DDI based upon references to cell lines and cell phenotypes. The results are in the form of fragments of sentences in which important concepts are visually highlighted. To determine the accuracy of the system, we used a gold standard of 5 expert curated articles. PD-Miner identified DDI with a recall of 75% and a precision of 46.55%. Along with the development of PD Miner, we also report development of a semantically annotated in vitro PD corpus. This corpus includes term and sentence level annotations and serves as a gold standard for future text mining

Semiautomatic generation of CORBA interfaces for databases in molecular biology

The amount and complexity of genome related data is growing quickly. This highly interrelated data is distributed at many different sites, stored in numerous different formats, and maintained by independent data providers. CORBA, the industry standard for distributed computing, offers the opportunity to make implementation differences and distribution transparent and thereby helps to combine disparate data sources and application programs. In this thesis, the different aspects of CORBA access to molecular biology data are examined in detail. The work is motivated by a concrete application for distributed genome maps. Then, the different design issues relevant to the implementation of CORBA access layers are surveyed and evaluated. The most important of these issues is the question of how to represent data in a CORBA environment using the interface definition language IDL. Different representations have different advantages and disadvantages and the best representation is highly application specific. It is therefore in general impossible to generate a CORBA wrapper automatically for a given database. On the other hand, coding a server for each application manually is tedious and error prone. Therefore, a method is presented for the semiautomatic generation of CORBA wrappers for relational databases. A declarative language is described, which is used to specify the mapping between relations and IDL constructs. Using a set of such mapping rules, a CORBA server can be generated automatically. Additionally, the declarative mapping language allows for the support of ad-hoc queries, which are based on the IDL definitions

Genomic data analysis using grid-based computing

Microarray experiments generate a plethora of genomic data; therefore we need techniques and architectures to analyze this data more quickly. This thesis presents a solution for reducing the computation time of a highly computationally intensive data analysis part of a genomic application. The application used is the Stanford Microarray Database (SMD). SMD\u27s implementation, working, and analysis features are described. The reasons for choosing the computationally intensive problems of the SMD, and the background importance of these problems are presented. This thesis presents an effective parallel solution to the computational problem, including the difficulties faced with the parallelization of the problem and the results achieved. Finally, future research directions for achieving even greater speedups are presented