IaaS and Science: How it works. Part 2

/ photo by Matteo Bagnoli CC

Last time, we started talking about the impact of IaaS technologies on various scientific fields of activity. Welcome to the second part of the post, where we will talk about how cloud computing helps to conduct research in biology, genetics, geography and medicine.
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Biology and genetics

One of the first and most famous cases of cloud distributed computing can be considered the project “Human Genome”, completed in 2003. His goal was to determine the sequence of DNA molecules and identify 25 thousand individual genes.

Genetic information collected during the project is stored in databases - it is a unique source of knowledge, analyzed by scientists of the world so far. The US National Center for Biotechnology Information and its partner organizations in Europe and Japan store genomic sequences in GenBank, the Japanese DNA Database (DDBJ) or the European EMBL. They hope that this information will help make new discoveries in the fields of genetics and bioengineering.

To maintain their work requires a large amount of computing resources. It is therefore not surprising that there is a need to change the technical approaches. The community turned to cloud technologies.

The main feature of cloud technologies, which is important for genomic informatics, is the ability to store huge sets of data in the cloud. Data is written to virtual disks, which can be connected to virtual machines as ordinary storage. To date, the entire GenBank database is stored as disk images that users download and unload at will.

Cloud computing has also affected the work of gene engineering related applications. They got the opportunity to present their products in the form of virtual machines. For example, many gene annotation groups have developed their own processes for identifying and classifying genes and other functional elements. For example, the University of California at Santa Cruz and Ensembl are engaged in supporting data and annotations, as well as tools for visualization and search in databases of genomic sequences.

Although many of the tools developed remained open, scientists had some difficulty transferring them to other research groups. This was primarily due to differences in program configurations and settings of individual sites. The cloud allowed to “package” the created applications into images of virtual machines - in this form, they are easy to transfer, configure and run, bypassing the software installation process.

Virtualization isolates users from infrastructure and provides flexibility in achieving goals. IaaS offers a full-featured computer infrastructure, providing all kinds of virtualized resources. An example of IaaS in the bioinformatics environment is the development of BioLinux — a public VM for high-performance computing — and the CLoVR — a portable VM for performing automatic sequencing.

Geography

Geographic Information Systems (GIS) is a set of tools that collect, store, analyze, manage, and formalize data related to geographic location. GIS plays an important role in many areas of activity and is a “fusion” of cartography, statistical analysis, hardware and software.

For data management, various methods of grouping and converting are used, for example, bringing geodata to a single scale. For their storage, relational databases with reporting technologies are used.

GIS allow you to query and analyze different complexity: from a simple search for objects on the map, to search for data using complex patterns, for example, the selection of settlements that fall into the affected area in the event of a nuclear accident.

The traditional result of processing, analyzing and displaying spatial geographic data is a map, which is complemented by reporting documents, embossed color images of real and modeled objects, photographs, graphs, diagrams.

In addition, modern GIS has a large number of special functions designed to make life easier for users. Some of them are used, including in navigation systems: finding the shortest path, laying a route, etc.



GIS is often used to make informed decisions based on geospatial data. Cloud implementation has opened up new horizons for researchers and IT organizations using geographic information systems.

Cloud GIS systems offer reliable tools that implement geoinformatics methods and powerful hardware and software: open access geographic servers, electronic map generation devices, and multivariate analysis algorithms. Moreover, the use of cloud technologies makes it possible to optimize the process of creating local GIS.

In this case, the company does not need to create a service center and buy its own expensive equipment and, therefore, it does not need to have talking IT staff. Also, there is no need to purchase space images and maps from third-party developers by connecting services such as Google Maps and Bing Maps.

All these advantages contribute to the massive transition to cloud technologies in the GIS environment. Organizations such as ESRI and GIS Cloud Ltd have already made the transition to cloud computing, offering users geo-information systems on demand.

Medicine and pharmacology

Cloud technology has also found its use in medicine. For example, the so-called electronic medical records are widespread in the world. An electronic medical record (EHR) stores all the necessary patient data in digital format on secure remote servers.

This facilitates the processing of personal data of patients, optimizes business processes: all medical institutions have access to a person’s medical history, which saves the latter from having to enter cards at each clinic.

According to a survey conducted by Accenture among 3,700 doctors in eight countries, 70.9% of respondents believe that information technology in medicine improves the quality of clinical research, and 69.1% noted an increase in the quality of medical care and a reduction in the number of medical errors. And this seems to be true. In US hospitals where EHRs are introduced, it takes much less time to treat a patient who was taken away in an ambulance.

Similar trends are observed in Europe. In the province of Andalusia, there is a global medical information system DIRAYA, built on Oracle infrastructure. This system is accessed by all medical institutions, receiving the necessary information about patients and current data on the course of treatment and prescribed medications.

Speaking of drugs. According to Accenture's research, an increasing number of companies in the chemical industry are starting to adapt cloud technologies. As an example, it is worthwhile to mention the Cyprotex QSAR application, which is used to automate decision making and to form predictive models. His goal is to create better and safer drugs and reduce the need for animal testing.

The search for quantitative structure-property relations (QSAR) is based on the use of mathematical statistics and machine learning methods for building models that allow predicting their physical and chemical properties by describing the structures of chemical compounds.

Unfortunately, the creation of a new model is a resource-intensive business, so chemists had to wait a long time for the results of processing. Cloud technology has revolutionized the use of QSAR, reducing the generation time of predictive models.

That's all. Cloud services over the past few years have penetrated into many areas of life and business, are used by small and large companies. In this series of posts, we have tried to consider the most interesting areas and examples of how cloud technologies help to conduct research.

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