BioJava is an open-source software project dedicated to provide Java tools to process biological data. BioJava is a set of library functions written in the programming language Java for manipulating sequences, protein structures, file parsers, Common Object Request Broker Architecture (CORBA) interoperability, Distributed Annotation System (DAS), access to AceDB, dynamic programming, and simple statistical routines. BioJava supports a huge range of data, starting from DNA and protein sequences to the level of 3D protein structures. The BioJava libraries are useful for automating many daily and mundane bioinformatics tasks such as to parsing a Protein Data Bank (PDB) file, interacting with Jmol and many more. This application programming interface (API) provides various file parsers, data models and algorithms to facilitate working with the standard data formats and enables rapid application development and analysis.
Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.
Mass spectrometry is a scientific technique for measuring the mass-to-charge ratio of ions. It is often coupled to chromatographic techniques such as gas- or liquid chromatography and has found widespread adoption in the fields of analytical chemistry and biochemistry where it can be used to identify and characterize small molecules and proteins (proteomics). The large volume of data produced in a typical mass spectrometry experiment requires that computers be used for data storage and processing. Over the years, different manufacturers of mass spectrometers have developed various proprietary data formats for handling such data which makes it difficult for academic scientists to directly manipulate their data. To address this limitation, several open, XML-based data formats have recently been developed by the Trans-Proteomic Pipeline at the Institute for Systems Biology to facilitate data manipulation and innovation in the public sector. These data formats are described here.
Ion mobility spectrometry (IMS) It is a method of conducting analytical research that separates and identifies ionized molecules present in the gas phase based on the mobility of the molecules in a carrier buffer gas. Even though it is used extensively for military or security objectives, such as detecting drugs and explosives, the technology also has many applications in laboratory analysis, including studying small and big biomolecules. IMS instruments are extremely sensitive stand-alone devices, but are often coupled with mass spectrometry, gas chromatography or high-performance liquid chromatography in order to achieve a multi-dimensional separation. They come in various sizes, ranging from a few millimeters to several meters depending on the specific application, and are capable of operating under a broad range of conditions. IMS instruments such as microscale high-field asymmetric-waveform ion mobility spectrometry can be palm-portable for use in a range of applications including volatile organic compound (VOC) monitoring, biological sample analysis, medical diagnosis and food quality monitoring. Systems operated at higher pressure are often accompanied by elevated temperature, while lower pressure systems (1-20 hPa) do not require heating.
Rudolf Aebersold is a Swiss biologist, regarded as a pioneer in the fields of proteomics and systems biology. He has primarily researched techniques for measuring proteins in complex samples, in many cases via mass spectrometry. Ruedi Aebersold is a professor of Systems biology at the Institute of Molecular Systems Biology (IMSB) in ETH Zurich. He was one of the founders of the Institute for Systems Biology in Seattle, Washington, where he previously had a research group.
The Trans-Proteomic Pipeline (TPP) is an open-source data analysis software for proteomics developed at the Institute for Systems Biology (ISB) by the Ruedi Aebersold group under the Seattle Proteome Center. The TPP includes PeptideProphet, ProteinProphet, ASAPRatio, XPRESS and Libra.
Mass spectrometry imaging (MSI) is a technique used in mass spectrometry to visualize the spatial distribution of molecules, as biomarkers, metabolites, peptides or proteins by their molecular masses. After collecting a mass spectrum at one spot, the sample is moved to reach another region, and so on, until the entire sample is scanned. By choosing a peak in the resulting spectra that corresponds to the compound of interest, the MS data is used to map its distribution across the sample. This results in pictures of the spatially resolved distribution of a compound pixel by pixel. Each data set contains a veritable gallery of pictures because any peak in each spectrum can be spatially mapped. Despite the fact that MSI has been generally considered a qualitative method, the signal generated by this technique is proportional to the relative abundance of the analyte. Therefore, quantification is possible, when its challenges are overcome. Although widely used traditional methodologies like radiochemistry and immunohistochemistry achieve the same goal as MSI, they are limited in their abilities to analyze multiple samples at once, and can prove to be lacking if researchers do not have prior knowledge of the samples being studied. Most common ionization technologies in the field of MSI are DESI imaging, MALDI imaging and secondary ion mass spectrometry imaging.
Galaxy is a scientific workflow, data integration, and data and analysis persistence and publishing platform that aims to make computational biology accessible to research scientists that do not have computer programming or systems administration experience. Although it was initially developed for genomics research, it is largely domain agnostic and is now used as a general bioinformatics workflow management system.
Label-free quantification is a method in mass spectrometry that aims to determine the relative amount of proteins in two or more biological samples. Unlike other methods for protein quantification, label-free quantification does not use a stable isotope containing compound to chemically bind to and thus label the protein.
The Proteomics Standards Initiative (PSI) is a working group of the Human Proteome Organization. It aims to define data standards for proteomics to facilitate data comparison, exchange and verification.
OpenMS is an open-source project for data analysis and processing in mass spectrometry and is released under the 3-clause BSD licence. It supports most common operating systems including Microsoft Windows, MacOS and Linux.
The OpenMS Proteomics Pipeline (TOPP) is a set of computational tools that can be chained together to tailor problem-specific analysis pipelines for HPLC-MS data. It transforms most of the OpenMS functionality into small command line tools that are the building blocks for more complex analysis pipelines. The functionality of the tools ranges from data preprocessing over quantitation to identification.
LabKey Server is a software suite available for scientists to integrate, analyze, and share biomedical research data. The platform provides a secure data repository that allows web-based querying, reporting, and collaborating across a range of data sources. Specific scientific applications and workflows can be added on top of the basic platform and leverage a data processing pipeline.
The Netherlands Bioinformatics for Proteomics Platform (NBPP) is joint initiative of the Netherlands Bioinformatics Centre (NBIC) and the Netherlands Proteomics Centre (NPC).
The PRIDE is a public data repository of mass spectrometry (MS) based proteomics data, and is maintained by the European Bioinformatics Institute as part of the Proteomics Team.
David Fenyö is a Swedish-American physicist and mass spectrometrist. He is currently professor in the Department of Biochemistry and Molecular Pharmacology at NYU Langone Medical Center. Fenyö's research focuses on the development of methods to identify, characterize and quantify proteins and in the integration of data from multiple modalities including mass spectrometry, sequencing and microscopy.
The Minimum Information Required About a Glycomics Experiment (MIRAGE) initiative is part of the Minimum Information Standards and specifically applies to guidelines for reporting on a glycomics experiment. The initiative is supported by the Beilstein Institute for the Advancement of Chemical Sciences. The MIRAGE project focuses on the development of publication guidelines for interaction and structural glycomics data as well as the development of data exchange formats. The project was launched in 2011 in Seattle and set off with the description of the aims of the MIRAGE project.
Skyline is an open source software for targeted proteomics and metabolomics data analysis. It runs on Microsoft Windows and supports the raw data formats from multiple mass spectrometric vendors. It contains a graphical user interface to display chromatographic data for individual peptide or small molecule analytes.
The 'German Network for Bioinformatics Infrastructure – de.NBI' is a national, academic and non-profit infrastructure initiated by the Federal Ministry of Education and Research funding 2015-2021. The network provides bioinformatics services to users in life sciences research and biomedicine in Germany and Europe. The partners organize training events, courses and summer schools on tools, standards and compute services provided by de.NBI to assist researchers to more effectively exploit their data. From 2022, the network will be integrated into Forschungszentrum Jülich.
