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Started by nilshomer, 05-08-2010, 02:19 PM
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52 responses
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by archana87
04-23-2019, 01:18 PM
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Started by anzdro, 07-18-2013, 10:26 AM
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2 responses
1,396 views
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by SNPsaurus
07-18-2013, 12:49 PM
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Started by The Spith, 07-17-2013, 02:21 AM
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1,557 views
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by The Spith
07-17-2013, 02:21 AM
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Started by rjames, 07-15-2013, 09:36 PM
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2 responses
2,440 views
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by rjames
07-16-2013, 05:14 AM
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Started by jhl667, 07-11-2013, 11:48 AM
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64 views
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by jhl667
07-11-2013, 11:48 AM
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Started by amylee86, 02-15-2013, 12:04 PM
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1 response
5,326 views
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by LB2301
07-10-2013, 07:50 AM
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Started by durandg, 05-15-2012, 02:11 AM
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4 responses
6,040 views
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by durandg
07-08-2013, 05:41 AM
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Started by wingtec, 07-07-2013, 03:44 PM
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1,588 views
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by wingtec
07-07-2013, 03:44 PM
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Started by medalofhonour, 07-02-2013, 11:06 AM
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3 responses
13,123 views
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by jparsons
07-05-2013, 08:40 AM
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Started by moosecakes, 07-04-2013, 06:48 AM
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1 response
3,139 views
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by sheenams
07-04-2013, 01:51 PM
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Started by Stephie, 07-04-2013, 07:49 AM
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by Stephie
07-04-2013, 07:49 AM
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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, Yesterday, 10:04 AM
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by SEQadmin2
Yesterday, 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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Started by SEQadmin2, 07-07-2026, 11:05 AM
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07-07-2026, 11:05 AM
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