4 Mistakes to Avoid in Biological Sequence Searches: Biological sequence search also called as Sequence Analysis is an important tool in the domain of bioinformatics to get relevant insights pertaining to organic molecules like DNA, RNA or proteins. In sequence analysis these organic molecules (DNA, RNA or proteins) are subjected to a wide range of analytical methods to understand its structures, features, functions and/or evolution.
With the advent of patent and intellectual property regime, sequence analysis or biological sequence search has become very important for pharmaceuticals, agro-chemicals, textiles and other companies to understand the biological function of a gene or the protein that it encodes so that they can prioritize their research work accordingly.
Biological Sequence searching is the most powerful method today for inferring the biological function of a gene (or the protein that it encodes) and with the rapid growth in biotechnology space, organizations are filing patents at a much faster rate than ever before. Bio-sequence search involves finding a specific arrangement of sequences in the patent or non-patent document to ensure that the intended invention is novel and safe to make investments.
However, while doing biological sequence searches we do a lot of mistakes those ought to be avoided and with this article we are going to list those mistakes.
Also you can read: Guide to novelty searches !
4 Mistakes to Avoid in Biological Sequence Searches
Under-utilizing annotation information – Undermining and underutilizing annotated data is one of the most crucial mistakes that we commit while doing a biological sequence search. Neglecting these fields and data could have serious legal and economic consequences on your investments and thus we need to search these data also. Annotated data are placed in various fields including bibliographic references, date of earliest publication and date of sequence disclosure.
Unearthing data beyond online databases – Popular databases like Public BLAST portals search only the most readily-accessible elements of the entire universe of genome data. Many important data are still locked in various other proprietary databases, graphic images and illustrations, print documents and desktop hard drives. It is important for searchers to refer these databases too and neglecting them could hamper the overall goal.
Making decisions based on yesterday’s results – Genome sequence information is extremely dynamic and thus it is important that the collected raw data is current and updated. Making decisions based on previous day’s data could be detrimental to your goal. A sequence data query affecting important scientific research and business decisions might not yield the same answer one week from now.
Choosing right algorithm for search – Every database works on the principle of different ranking algorithms and thus we need to understand various limitations that a database can have. We also need to create search strings that targeted specifically to a database. For example, using BLAST for short sequences will miss many approximate hits and thus we need to rely on other databases working on the different algorithmic model.
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In relation to the context, we have our another article based upon the chemical structure and its databases. Click here to read !