Pre-genomics training hinders Indian biotech
نویسندگان
چکیده
منابع مشابه
Will genomics guide a greener forest biotech?
Forest biotechnology has been increasingly associated with wood production using plantation forestry, and has stressed applications that use pedigreed material and transgenic trees. Reasons for this emphasis include limitations of available technologies to conform to underlying genetic features of undomesticated forest tree populations. More recently, genomic technologies have rapidly begun to ...
متن کاملBiotech Meets Chemistry: Roche Invests in Customized Training.
In response to current needs, Roche is offering its employees an intensive course in biotechnology under the auspices of biotechnet Switzerland. Lecturers from ZHAW Wädenswil [university of applied science] give participants the benefit of their expertise in theory and laboratory practice. One valuable spin-off from this is that this extra-mural course will allow participants to create a perman...
متن کاملThe Rio1p ATPase hinders premature entry into translation of late pre-40S pre-ribosomal particles
Cytoplasmic maturation of precursors to the small ribosomal subunit in yeast requires the intervention of a dozen assembly factors (AFs), the precise roles of which remain elusive. One of these is Rio1p that seems to intervene at a late step of pre-40S particle maturation. We have investigated the role played by Rio1p in the dynamic association and dissociation of AFs with and from pre-40S part...
متن کاملFunctional genomics of human pre-implantation development.
Early mammalian embryogenesis is currently the focus of intense interest because of the potential of inner cell mass-derived embryonic stem cell lines in new therapeutic strategies. As such, creating molecular profiles of gene expression during pre-implantation development will provide a framework for understanding the biological properties of these cells and also establish a tool set for subse...
متن کاملPre-training Attention Mechanisms
Recurrent neural networks with differentiable attention mechanisms have had success in generative and classification tasks. We show that the classification performance of such models can be enhanced by guiding a randomly initialized model to attend to salient regions of the input in early training iterations. We further show that, if explicit heuristics for guidance are unavailable, a model tha...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nature
سال: 2003
ISSN: 0028-0836,1476-4687
DOI: 10.1038/422802a