Some of the scientific softwares are integrated within the instruments such as PCR machines, flow cytometers, Genome Sequencing machines etc., making it easier to generate as well as analyze the data simultaneously. Data analysis in the life sciences has two arms: analysis and graphical representation. Usually, the software supplied with the instrument are not finely tuned for publication quality graphical representation. Sometimes, these softwares are also restricted to particular file formats or instrument specific data, thereby not allowing analysis of data from any other sources. This then paves way for third party softwares that rid of such limitations. One should take care of following points while selecting a third party software.
Validated and Benchmarked algorithm:
This is the most important criterion in the selection of scientific software. A high number of citations of particular software in a number of different quality journals indicate towards the robustness and weightage to the algorithm of the software. In this process, the algorithm gets validated and benchmarked when the results are reviewed by various journals and allowed to publish based on the quality of data produced. At TechnoConcept we work with Lasergene, which has been cited in more than 50,000 research papers and 1500 different quality journals. HyperChem is Reference Software for molecular modelling in various US Universities. High acceptance of data produced by SAS statistical software by FDA was one of the reasons. Another advantage of such software is that a lot of research journals give easy acceptance to the data analyzed by the software, which has high citation index.
Acceptance to file formats:
Third-party software must accept as many file formats as possible. One should get through the list of formats provided by the software company. The software should comply with the data formats provided by all possible machines in that particular technology.
Background of the Developer Company:
This is a very important part, which is overlooked by most of the young buyers. The area experts of those field and quality software developers should back up a developer company. We know renowned scientist from the University of Wisconsin, Fred Blackener who sequenced E.coli bacteria for the first time, founded DNASTAR around 30 years ago and since then the company is working with a focused approach to providing DNA and Protein Sequence Analysis software which has almost 80,000 Users worldwide. Similarly, Dr Neil Ostlund was a faculty member and the director of the computer architecture lab in the computer science department of the University of Waterloo. In 1987, Dr Ostlund left the University of Waterloo to work full-time for Hypercube, hiring its first full-
time employees. Hypercube keeps updating molecular modelling algorithms of its highly recognized software Hyperchem. These companies have neither been sold nor merged with any bigger companies and their support is wonderful to the researchers and scholars. A company like VectorNTI did not have any such background, was later sold to Thermofisher and subsequently
lost its market value. Licensing Options and updates Software gets redundant if not upgraded with time and changing technologies. Therefore it is important to have a look at the particular software which one decides must have a history of regular updates and upgrades.
One should also be careful while deciding on the type of License like annual, cloud-based or perpetual. Although Cloud-based and annually licensed based software is updated automatically but perpetual licensing based software needs updates or upgrades at certain intervals, else changing Internet technologies and core technologies don’t synchronize with software to sustain for a long time.
Freeware Vs Commercial Software:
There is plenty of freeware scientific software which are available on the Internet to analyze data those cannot sustain for a longer time due to high cost involved in the development of up-gradations. Also, freeware cannot use some of the patented algorithms. DNASTAR provide Novafold for using ITASSR technologies for creating imprints of 3-D predictions where eachimprint cost money. Most of the commercial software meets with above-mentioned parameters however freeware can not.
Operating Systems:
In Life Sciences data analysis segment, there are two approaches, based on the expertise level. One segment comprises of Bioinformaticians who prefer working with Linux based software due to very high flexibility of programming. On the other hand, Biologists prefer analyzing data on Windows or Mac which doesn’t need any programming skill and data can be analyzed in minutes with a bundle of features. Hence, software tools should be selected based on the type of OS it is most compatible with and the level of expertise of the user as well.
Written by Rakesh Arora, CEO, TechnoConcept India Pvt Ltd
Information Courtesy www.dnastar.com and www.hyper.com
Image courtesy - keramidas
