Titlebook: Research in Computational Molecular Biology; 22nd Annual Internat Benjamin J. Raphael Conference proceedings 2018 Springer International Pu

劇本

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Loss-Function Learning for Digital Tissue Deconvolution, following inverse problem: Given the expression profile . of a tissue, what is the cellular composition . of that tissue? If . is a matrix whose columns are reference profiles of individual cell types, the composition . can be computed by minimizing . for a given loss function .. Current methods us

Commodious

ANN

chemoprevention

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Constrained , Sequencing of neo-Epitope Peptides Using Tandem Mass Spectrometry,epitope peptides are recognized and subsequently killed by cytotoxic T-cells. . approaches aim to characterize the peptide repertoire (including neoepitope) associated with the MHC-I molecules on the surface of tumor cells using proteomic technologies, providing critical information for designing ef

富饒

Reverse de Bruijn: Utilizing Reverse Peptide Synthesis to Cover All Amino Acid ,-mers,prehensive picture of the binding spectrum is obtained. Researchers would like to measure binding to the longest .-mer possible, but are constrained by the number of peptides that can fit into a single microarray. A key challenge is designing a minimum number of peptides that cover all .-mers. Here,

anagen

節(jié)約

clarify

Context-Specific Nested Effects Models,etabolism, and cellular signaling. A common approach to uncovering biological networks involves performing perturbations on elements of the network, such as gene knockdown experiments, and measuring how the perturbation affects some reporter of the process under study. In this paper, we develop cont