生物信息学技术

In proteomic studies, liquid chromatography coupled with mass spectrometry (LC-MS) is a common platform to compare the abundance of various peptides that characterize particular proteins in biological samples. Each LC-MS run generates data consisting of thousands of peak intens ...

The rapid growth of protein sequence databases has necessitated the development of methods to computationally derive annotation for uncharacterized entries. Most such methods focus on “global” annotation, such as molecular function or biological process. Methods to supply hig ...

The LC-MS/MS shotgun proteomics workflow is widely used to identify and quantify sample peptides and proteins. The technique, however, presents a number of challenges for large-scale use, including the diverse raw data file formats output by mass spectrometers, the large false positive r ...

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for ana ...

With the advent of more powerful and sensitive analytical techniques and instruments, the field of mass spectrometry based proteomics has seen a considerable increase in the amount of generated data. Correspondingly, the need to make these data publicly available in centralized onli ...

It is now becoming more usual for journals to request the submission of the data accompanying an article to an appropriate public repository. Such users may access the data in a format appropriate for display and reanalysis. It is commonly accepted that molecular interaction databases will ho ...

With the continuously growing amount of proteomics data being produced, it has become increasingly important to make these data publicly available so that they can be audited, reanalyzed, and reused. More and more journals are also starting to request the deposition of MS data in publicly avai ...

This chapter describes using the Protein Inference Engine (PIE) to integrate various types of data – especially top down and bottom up mass spectrometer (MS) data – to describe a protein’s posttranslational modifications (PTMs). PTMs include cleavage events such as the n-terminal loss of me ...

Bottom-up and top-down strategies are two commonly used methods for mass spectrometry (MS) based protein identification; each method has its own advantages and disadvantages. In this chapter, we describe an integrated top-down and bottom-up approach facilitated by concurrent liqu ...

The success of mass spectrometry based proteomics depends on efficient methods for data analysis. These methods require a detailed understanding of the information value of the data. Here, we describe how the information value can be elucidated by performing simulations using synthe ...

Protein identification from tandem mass spectra is one of the most versatile and widely used proteomics workflows, able to identify proteins, characterize post-translational modifications, and provide semi-quantitative measurements of relative protein abundance. This m ...

In the past decades, a variety of publicly available data repositories and resources have been developed to support protein related information management, data-driven hypothesis generation and biological knowledge discovery. However, there is also an increasing confusion f ...

Improvements in nucleotide sequencing technology have resulted in an ever increasing number of nucleotide and protein sequences being deposited in databases. Unfortunately, the ability to manually classify and annotate these sequences cannot keep pace with their rapid genera ...

One of the essential requirements of the proteomics community is a high quality annotated nonredundant protein sequence database with stable identifiers and an archival service to enable protein identification and characterization. The scope of this chapter is to illustrate how U ...

Proteomics has advanced in leaps and bounds over the past couple of decades. However, the continuing dependency of mass spectrometry-based protein identification on the searching of spectra against protein sequence databases limits many proteomics experiments. If there is no sequ ...

The review describes methods of de novo sequencing of peptides by mass spectrometry. De novo methods utilize computational approaches to deduce the sequence or partial sequence of peptides directly from the experimental MS/MS spectra. The concepts behind a number of de novo sequencing m ...

Spectral library searching is a new approach in proteomic data analysis that promises to address some of the shortcomings of sequence database searching, currently the dominant method for inferring peptide identifications from tandem mass spectra. In spectral searching, a spectr ...

Tandem mass spectrometry is a widely used tool in proteomics. This section will address the properties that describe how protonated peptides fragment when activated by collisions in a mass spectrometer and how that information can be used to identify proteins. A review of the mobile proton mo ...

Accurate and precise methods for estimating incorrect peptide and protein identifications are crucial for effective large-scale proteome analyses by tandem mass spectrometry. The target-decoy search strategy has emerged as a simple, effective tool for generating such estima ...

A variety of methods are described in the literature to assign peptide sequences to observed tandem MS data. Typically, the identified peptides are associated only with an arbitrary score that reflects the quality of the peptide-spectrum match but not with a statistically meaningful sig ...