The Bioinformatics Computing Laboratory (BCL) serves as a core facility for the Border Biomedical Research Center (BBRC). Our panel of consulting faculty from the departments of Biological Sciences, Chemistry, Computer Science, Electrical and Computer Engineering, and Mathematical Sciences provide bioinformatics computing support on a broad spectrum of research projects. We specialize in developing databases and software for: genomics and proteomics data analysis; biomolecular sequence analysis and structure prediction; and glycosylation site prediction. We aid researchers in the use of these advanced bioinformatics software tools by building user-friendly, customized, web-based interfaces for them. Processing power to support the robust computational and analytical operations of the BCL are provided by a powerful network of local and regional high-performance computing facilities.
Member:
Agrawal, Akshay, Ph.D.
Role:
Assistant Director, Bioinformatics Program
Member:
Cardenas, Gerardo, Ph.D.
Role:
Bioinformatics Systems Administrator
"PseudoBase++ is a searchable up-to-date database of the PseudoBase pseudoknots wrapped by a versatile, user-friendly interface providing scientists with a powerful engine to access, search, select, and sort data based on different fine-grained criteria. The PseudoBase++ interface allows scientists to visualize selected structures with PseudoViewer, to map existing sequences to GenBank, and to insert new pseudoknots to the PseudoBase dataset through a syntax-controlled interface that prevents structural error for long sequences. PseudoBase++ is part of the RNAVLab project a virtual laboratory for the analysis of RNA secondary structures and serves the specific purpose of facilitating analysis of pseudoknots."
Bioinformatics program main server that provides an internal network service. Grid computing capacity
Our server allows DNA core users to manipulate DNA sequencing data by facilitating sequence alignment, sequence editing, DNA assembly as well as tools for microarray analysis, structure prediction and statistical analysis. This computer allows for rapid analysis of output data from other instruments.
This server is used to run the computational tool for large-scale
GPIomic analysis. This tool aims to identify GPI molecules given mass spectrometry data
This computer is used mainly for prediction of o-glycosylation sites on amino acid sequences.
Ribonucleic Acid Virtual Laboratory for Sequence Analysis, Structure Prediction, and Databases
General Bioinformatics Computing Support provided by various faculty members in the areas of:
* Cancer Informatics
* Computational Biology
* Cryo-EM data analysis
* Data Processing Under Uncertainty
* Demographic Analysis
* DNA Sequencing
* Glycosylation Site Prediction
* Epidemiology
* Evolution
* Genome Sequence Assembly
* Intelligent Data Processing
* Machine Learning
* Macromolecule Assembly
* Mass Spectrometry
* Medical Imaging
* Microarray Analysis
* Molecular Sequence Analysis
* Optimization
* Phylogenetic Analysis
* Population Genetics
* Probabilistic Modeling
* Protein Structure Prediction
* Proteomics
* RNA Structures
* Sequence Assembly
* Statistical Genetics
* Toxicogenomics
* Viral Genomics
* X-ray Crystallography
Software Development and Computational Modeling provided by various faculty members in the areas of:
* Cancer Biomarker Analysis
* Cancer Informatics
* Computational Biology
* Cryo-EM data analysis
* Data Processing Under Uncertainty
* Demographic Analysis
* DNA Sequencing
* Glycosylation Site Prediction
* Epidemiology
* Evolution
* Genome Sequence Assembly
* Intelligent Data Processing
* Machine Learning
* Macromolecule Assembly
* Mass Spectrometry
* Medical Imaging
* Microarray Analysis
* Molecular Sequence Analysis
* Optimization
* Phylogenetic Analysis
* Population Genetics
* Probabilistic Modeling
* Protein Structure Prediction
* Proteomics
* RNA Structures
* Sequence Assembly
* Statistical Genetics
* Toxicogenomics
* Viral Genomics
* X-ray Crystallography
"To analyze the sequence either upload a file with the sequences in FASTA format, or copy and paste the sequence(s) inside the text area [on the website]."