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Is there some good software to automatically annotate a DNA sequence? I'm dealing with a specific situation right now, but it would be nice to have a general tool that just takes a DNA sequence and automatically annotates it well based on information from databases. In my situation right now, I am looking at chimeric transcripts in cancer cells where two transcripts from different genes are fused together. Therefore, I get a sequence, blast it, find out which part matches with transcript A, find out which part matches with transcript B, and then I annotate it using APE (Advanced Plasmid Editor) to mark which part of the sequence corresponds to transcript A and B, the start codon, the stop codon. I can then acquire some useful information such as the protein produced, and the protein sequence after the fusion point. Anyway, does anyone have a good recommendation for automatically annotating DNA sequences?
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Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
...07-09-2026, 11:10 AM -
Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...07-08-2026, 05:17 AM -
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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