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Techniques and protocol discussions on sample preparation, library generation, methods and ideas
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Started by steuerna, 05-14-2010, 06:26 AM
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1 response
2,156 views
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by krobison
05-17-2010, 10:43 AM
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Started by sdavis, 04-29-2010, 11:17 AM
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12 responses
10,941 views
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by upenn_ngs
05-14-2010, 10:39 AM
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Started by Melanie, 05-12-2010, 12:38 PM
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2 responses
3,524 views
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by bioinfosm
05-13-2010, 09:54 AM
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Started by peromhc, 05-01-2010, 02:20 AM
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1 response
3,808 views
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by peromhc
05-12-2010, 09:03 AM
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Started by pDNA, 05-10-2010, 08:06 AM
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0 responses
2,524 views
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Last Post
by pDNA
05-10-2010, 08:06 AM
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Started by polystone, 05-04-2010, 10:07 AM
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0 responses
3,586 views
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by polystone
05-04-2010, 10:07 AM
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Started by rodr08, 03-26-2010, 07:06 AM
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3 responses
10,588 views
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by rodr08
05-03-2010, 10:36 AM
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Started by H5N1, 01-18-2010, 10:21 PM
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5 responses
10,696 views
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by nextgen
05-03-2010, 10:34 AM
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Started by krelmer, 03-30-2010, 12:33 AM
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3 responses
3,521 views
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by nextgen
05-03-2010, 09:28 AM
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Started by ymc, 04-26-2010, 07:48 PM
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6 responses
3,041 views
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Last Post
by ymc
04-27-2010, 06:21 PM
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by SEQadmin2
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.
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by SEQadmin2
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...-
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07-08-2026, 05:17 AM -
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by GATTACATLove 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.
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07-01-2026, 11:43 AM -
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Started by SEQadmin2, 07-13-2026, 10:26 AM
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by SEQadmin2
07-13-2026, 10:26 AM
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Started by SEQadmin2, 07-09-2026, 10:04 AM
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by SEQadmin2
07-09-2026, 10:04 AM
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Started by SEQadmin2, 07-08-2026, 10:08 AM
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07-08-2026, 10:08 AM
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