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Techniques and protocol discussions on sample preparation, library generation, methods and ideas
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Started by aperera, 12-14-2011, 07:36 AM
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1 response
2,032 views
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by CMF_Ron
06-15-2012, 06:28 AM
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Started by HeidiJTP, 06-12-2012, 07:11 AM
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2 responses
2,992 views
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by HeidiJTP
06-14-2012, 06:13 AM
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Started by dhanapala, 06-13-2012, 10:41 AM
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1 response
2,266 views
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by NormSci
06-13-2012, 12:15 PM
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Started by a.cardilini, 04-03-2012, 05:43 PM
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2 responses
4,320 views
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by jboone123
06-12-2012, 04:43 PM
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Started by carotylene, 06-12-2012, 12:42 AM
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3 responses
2,809 views
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by pmiguel
06-12-2012, 05:29 AM
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Started by Eli Boritz, 06-05-2012, 01:33 PM
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2 responses
2,826 views
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by protist
06-11-2012, 08:08 AM
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Started by shawpa, 06-11-2012, 06:23 AM
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0 responses
1,822 views
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by shawpa
06-11-2012, 06:23 AM
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Started by einarr, 06-06-2012, 03:34 AM
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0 responses
3,522 views
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by einarr
06-06-2012, 03:34 AM
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Started by snapper, 11-12-2010, 07:34 AM
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2 responses
3,532 views
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by hbn
06-05-2012, 10:31 PM
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Started by Lj Lee, 04-01-2012, 06:16 PM
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8 responses
2,907 views
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Last Post
by hbn
06-05-2012, 10:19 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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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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