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Pyrosequencing in picotiter plates, custom arrays for enrichment/decomplexing. (Roche)
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Started by ECO, 11-05-2007, 11:40 PM
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by chelseaclark
02-25-2022, 10:51 PM
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Started by ECO, 12-29-2008, 08:55 PM
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26 responses
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by ParkerKB
01-12-2012, 07:04 AM
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Started by ECO, 09-27-2008, 05:28 PM
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11 responses
56,910 views
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by pmiguel
09-11-2011, 07:10 AM
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Started by kingbiotech, 12-29-2009, 10:33 PM
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2,348 views
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by kingbiotech
12-29-2009, 10:33 PM
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Started by animesh, 02-29-2008, 07:25 AM
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21 responses
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by sklages
12-26-2009, 07:22 AM
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Started by bioinfosm, 10-15-2008, 10:55 AM
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by Tuxido
12-23-2009, 04:35 AM
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Started by joa_ds, 04-09-2009, 03:15 AM
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by pmiguel
12-18-2009, 11:33 AM
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Started by LMcSeq, 12-16-2009, 12:41 PM
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3 responses
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by Hamid
12-17-2009, 11:10 AM
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Started by krelmer, 11-13-2009, 06:00 AM
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9 responses
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by pmiguel
12-16-2009, 06:35 AM
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Started by boss_hoss, 12-14-2009, 09:00 AM
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by boss_hoss
12-14-2009, 09:00 AM
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Started by pmiguel, 12-07-2009, 09:29 AM
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by joa_ds
12-14-2009, 08:14 AM
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Started by anabio, 12-09-2009, 05:49 PM
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by pmiguel
12-11-2009, 07:37 AM
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Started by pmiguel, 11-05-2009, 06:04 AM
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9 responses
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by seqAll
12-04-2009, 09:59 AM
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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.
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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.
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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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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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