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Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc
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04-09-2015, 06:50 AM
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04-09-2015, 05:58 AM
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04-09-2015, 03:00 AM
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04-08-2015, 07:48 AM
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04-08-2015, 07:44 AM
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04-08-2015, 06:51 AM
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04-08-2015, 03:30 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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