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Input Data of Biological Problems
I am a newbie in bioinformatics and am coming from computer science angle, where developing models/algorithms/programs to solve biological problem is our focus. I want to ask if there is any data input to programs apart from DNA and Protein sequence, especially in developing Gene Regulatory Network or any Biological Process Network
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Have a look at microarray and/or RNAseq datasets (e.g., via GEO). You can then extract expression covariation metrics and construct convenient networks (biological process networks would likely be subnetworks thereof). Those types of datasets would also allow construction of regulatory networks, depending on the dataset. -
Thanks, I will look into it. More Grace.........Comment
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Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.07-01-2026, 11:43 AM
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...
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