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Bioinformatics is the intersection of computer science, statistics, molecular biology and genetics. It is one of the most important emerging research areas of the 21st century and has already attracted worldwide interest. It is clear that major initiatives are being undertaken which will establish Australia both as a vital link in the international bioinformatics community for research and development and also as an Asia-Pacific service for bioinformatics. This article briefly notes some groups carrying out bioinformatics research in Australia.

This paper presents a brief overview of intellectual property rights and the various areas in proteomics to which IP rights may be applicable. Technology transfer, including licensing and business agreements, is not covered in this paper. Instead, issues and complications that are related to national and overseas patent prosecution in this relatively new field would be discussed.

Competitive Positioning Strategies for Australian Biotech Companies A Road Map to Achieve Competitive Position in the Global Biotech Marketplace Part III — Australia: Current Position and Key Success Factors.

The article discusses about the potential of Australia and New Zealand biotechnology opportunities.

The article is a summary of the research done in GIS. It touches on the focus on systems and integrative biology and GIS's efforts in collaborating with international organizations.

University of Queensland Offers Biotech Scholarship to Indian Students.

Australian Government Contributes $50M to Walter and Eliza Hall Institute.

US Pharmacy Giant MedicineShoppe Opens its First Store in China's ChongQing.

Pall Life Science Sets up Proteomics Center at Bangalore.

Hong Kong and Guangdong Health Experts to Collaborate on Bird Flu Lab Testing.

Taiwan's Vita Genomics, Yang Ming University and India's IGIB Sign Agreement on Liver Disease Research.

Update on Bird flu.

Singapore Scientists Make Discoveries on Stomach Cancer.

US Imalux Corporation Inks Distribution Deals with Beijing Goodwell Company Limited.

Australia's CSL Expansion Facility and Vaccine Market.

India and the US Collaborate on Agriculture.

Korea's Professor Hwang's Fabrication of Embryonic Stem Cell Research.

Cygenics Awarded Another Patent.

Brisbane-based Alchemia Merge with Melbourne-based Meditech.

Imugene to Conduct Second Bird Flu Program.

LCT and The Bionic Ear Institute Collaborate on Research to Improve Hearing Loss.

Norwood Abbey takes MIT's Needle Licence.

Sinovac Biotech and LG Life Sciences Announce Distribution Agreement to Market Vaccines in China.

Novavax and Bharat Biotech to Co-develop Flu Vaccine.

Perth-based Proteomics Partners with New Delhi-based TechnoConcept.

Japan's Bioventures Today — A-Cube Inc.

SGS Opens Up New Contract Analytical Laboratory for Quality Control Testing in Singapore.

CyGenics Expands Into Europe.

Increasing US Investment Support for Starpharma.

Proteomics — An Australian-based Biotech Company.

Resonance Health to Expand US Business Operations.

Rockeby biomed Announces Four New Developments for Avian Influenza Test Kits.

Ranbaxy Buys Companies in Belgium, Italy and Romania.

Japan's Bioventures Today — HuBit Genomix Inc.

Abbott to Invest US$280 Million in the Largest Nutritional Plant in Singapore.

Covance Celebrates 10th Anniversary Milestone in Singapore.

NanoMaterials Technology Opens New S$2.5 Million Facility.

Waters Corporation Collaborates with Solectron.

Zentek Engineering Becomes First Irish Company to Set Up Asia Pacific HQ in Singapore.

Drug Discovery in China.

Pharmaceutical Industrial Partnering Trends in India.

CS Trail Closure Statement Unaffects VivaGel™ Clinical Trails Progress.

Living Cell Technologies to Run World's First Xenotransplantation Trial in Diabetes without Immunosuppression.

China Medical Technologies Inc—A Medical Device Company.

Sinovac Biotech to Increase Stake in China Subsidiary.

Aurigene Collaborates With Forest Labs.

Transgene Biotek Developing Oral Vaccine to Fight Diabetes.

ImClone and Bristol-Myers Team up for Cancer Treatment in Japan.

Japan Bioventures Today—Medical ProteoScope Co Ltd.

Fluidigm Launches Biomedical Product Development Center.

Singular ID Launches Enxure On-Line Portal with the Delivery of Two Enxure Evaluation Kits.

Exploring the Role of Glutathione in the Regulation of Immune Cell Function.

Does Oxidative Damage Cause Poor Healing?

Pathogenesis of Atopic Dermatitis in Singapore.

Proteomics and Colorectal Cancer Metastasis: Bird's-Eye View on Current Scenario and Our Contribution.

Zebrafish: A Small Fish Model for a Big Human Disease.

The Reign of a New Dictator: Circulating MicroRNA in Diabetes.

Engineering Artificial Vascularized Bone Grafts for the Repair of Large Bone Defects.

A 'Nano' Era for Blood Glucose Sensing.

Ancient Medicine with Newer Roles: Potential Role of Celastrol in the Treatment of Multiple Myeloma.

Proteins, Proteome and Proteomics.

A Novel Promising Biomarker and Therapy Target of Liver Cancer.

P&G Children's Safe Drinking Water Program Celebrates 10 Billion Litre Milestone in Singapore.

New In-Vitro Studies Reinforce Efficacy of BETADINE® Skin Cleanser against Viruses that Cause Hand Foot & Mouth Disease.

Singapore Ranked Fifth in its Readiness to Achieve a Fully Integrated Health System Reveals First Future Health Index.

SCIEX Announces High Throughput, Industrialised Omics Solutions.

Novartis Expands Partnership with Medicines for Malaria Venture to Develop Next-Generation Antimalarial Treatment.

ADVA Launches Dengue Mission Buzz Barometer Tool to Boost Critical Dengue Prevention Awareness and Preparedness Amongst ASEAN Community.

Innovative Diagnostics Awarded Unprecedented Westgard Sigma Certification in Singapore.

Proteomics research programs typically comprise the identification of protein content of any given cell, their isoforms, splice variants, post-translational modifications, interacting partners and higher-order complexes under different conditions. These studies present significant analytical challenges owing to the high proteome complexity and the low abundance of the corresponding proteins, which often requires highly sensitive and resolving techniques. Mass spectrometry plays an important role in proteomics and has become an indispensable tool for molecular and cellular biology. However, the analysis of mass spectrometry data can be a daunting task in view of the complexity of the information to decipher, the accuracy and dynamic range of quantitative analysis, the availability of appropriate bioinformatics software and the overwhelming size of data files. The past ten years have witnessed significant technological advances in mass spectrometry-based proteomics and synergy with bioinformatics is vital to fulfill the expectations of biological discovery programs. We present here the technological capabilities of mass spectrometry and bioinformatics for mining the cellular proteome in the context of discovery programs aimed at trace-level protein identification and expression from microgram amounts of protein extracts from human tissues.

As whole genome sequences continue to expand in number and complexity, effective methods for comparing and categorizing both genes and species represented within extremely large datasets are required. Methods introduced to date have generally utilized incomplete and likely insufficient subsets of the available data. We have developed an accurate and efficient method for producing robust gene and species phylogenies using very large whole genome protein datasets. This method relies on multidimensional protein vector definitions supplied by the singular value decomposition (SVD) of a large sparse data matrix in which each protein is uniquely represented as a vector of overlapping tetrapeptide frequencies. Quantitative pairwise estimates of species similarity were obtained by summing the protein vectors to form species vectors, then determining the cosines of the angles between species vectors. Evolutionary trees produced using this method confirmed many accepted prokaryotic relationships. However, several unconventional relationships were also noted. In addition, we demonstrate that many of the SVD-derived right basis vectors represent particular conserved protein families, while many of the corresponding left basis vectors describe conserved motifs within these families as sets of correlated peptides (copeps). This analysis represents the most detailed simultaneous comparison of prokaryotic genes and species available to date.

The precise excision of introns from mRNAs is executed by the spliceosome, a cellular machinery composed by five small nuclear RNAs and hundreds of proteins. In the last few years, several groups have used proteomics and computational biology tools to characterize the components of the human spliceosome. These reports have identified basically all known splicing factors and several new proteins. The composition of the human spliceosome confirms the link between splicing and other steps in gene expression. Here we comment on these reports and discuss the perspectives for the coming years.

In proteomics, tandem mass spectrometry is the key technology for peptide sequencing. However, partially due to the deficiency of peptide identification software, a large portion of the tandem mass spectra are discarded in almost all proteomics centers because they are not interpretable. The problem is more acute with the lower quality data from low end but more popular devices such as the ion trap instruments.

In order to deal with the noisy and low quality data, this paper develops a systematic machine learning approach to construct a robust linear scoring function, whose coefficients are determined by a linear programming. A prototype, PRIMA, was implemented. When tested with large benchmarks of varying qualities, PRIMA consistently has higher accuracy than commonly used software MASCOT, SEQUEST and X! Tandem.

Cisplatin-induced drug resistance is known to involve a complex set of cellular changes whose molecular mechanism details remain unclear. In this study, we developed a systems biology approach to examine proteomics- and network-level changes between cisplatin-resistant and cisplatin-sensitive cell lines. This approach involves experimental investigation of differential proteomics profiles and computational study of activated enriched proteins, protein interactions, and protein interaction networks. Our experimental platform is based on a Label-free liquid Chromatography/mass spectrometry proteomics platform. Our computational methods start with an initial list of 119 differentially expressed proteins. We expanded these proteins into a cisplatin-resistant activated sub-network using a database of human protein-protein interactions. An examination of network topology features revealed the activated responses in the network are closely coupled. By examining sub-network proteins using gene ontology categories, we found significant enrichment of proton-transporting ATPase and ATP synthase complexes activities in cisplatin-resistant cells in the form of cooperative down-regulations. Using two-dimensional visualization matrixes, we further found significant cascading of endogenous, abiotic, and stress-related signals. Using a visual representation of activated protein categorical sub-networks, we showed that molecular regulation of cell differentiation and development caused by responses to proteome-wide stress as a key signature to the acquired drug resistance.

Determining glycan structures is vital to comprehend cell-matrix, cell-cell, and even intracellular biological events. Glycan sequencing, which determines the primary structure of a glycan using tandem mass spectrometry (MS/MS), remains one of the most important tasks in proteomics. Analogous to peptide de novo sequencing, glycan de novo sequencing determines the structure without the aid of a known glycan database. We show in this paper that glycan de novo sequencing is NP-hard. We then provide a heuristic algorithm and develop a software program to solve the problem in practical cases. Experiments on real MS/MS data of glycopeptides demonstrate that our heuristic algorithm gives satisfactory results on practical data.

Tandem mass spectrometry (MS/MS) combined with protein database searching has been widely used in protein identification. A validation procedure is generally required to reduce the number of false positives. Advanced tools using statistical and machine learning approaches may provide faster and more accurate validation than manual inspection and empirical filtering criteria. In this study, we use two feature selection algorithms based on random forest and support vector machine to identify peptide properties that can be used to improve validation models. We demonstrate that an improved model based on an optimized set of features reduces the number of false positives by 58% relative to the model which used only search engine scores, at the same sensitivity score of 0.8. In addition, we develop classification models based on the physicochemical properties and protein sequence environment of these peptides without using search engine scores. The performance of the best model based on the support vector machine algorithm is at 0.8 AUC, 0.78 accuracy, and 0.7 specificity, suggesting a reasonably accurate classification. The identified properties important to fragmentation and ionization can be either used in independent validation tools or incorporated into peptide sequencing and database search algorithms to improve existing software programs.

In proteomics, useful signal may be unobserved or lost due to the lack of confident peptide-spectral matches. Selection of differential spectra, followed by associative peptide/protein mapping may be a complementary strategy for improving sensitivity and comprehensiveness of analysis (spectra-first paradigm). This approach is complementary to the standard approach where functional analysis is performed only on the finalized protein list assembled from identified peptides from the spectra (protein-first paradigm). Based on a case study of renal cancer, we introduce a simple spectra-binning approach, MZ-bin. We demonstrate that differential spectra feature selection using MZ-bin is class-discriminative and can trace relevant proteins via spectra associative mapping. Moreover, proteins identified in this manner are more biologically coherent than those selected directly from the finalized protein list. Analysis of constituent peptides per protein reveals high expression inconsistency, suggesting that the measured protein expressions are in fact, poor approximations of true protein levels. Moreover, analysis at the level of constituent peptides may provide higher resolution insight into the underlying biology: Via MZ-bin, we identified for the first time differential splice forms for the known renal cancer marker MAPT. We conclude that the spectra-first analysis paradigm is a complementary strategy to the traditional protein-first paradigm and can provide deeper level insight.