899 resultados para binary to multi-class classifiers
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Mode of access: Internet.
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On spine: Elementary English.
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Mode of access: Internet.
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Mode of access: Internet.
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Annotated bibliography: p. 8-35.
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The BZLF1 antigen of Epstein-Barr virus includes three overlapping sequences of different lengths that conform to the binding motif of human leukocyte antigen (HLA) B*3501. These 9-mer ((56)LPOGQLTAy(64)), 11-mer ((54)EPLPQGQLTAy(64)), and 13-mer ((52)LPEPLPQGQLTAY(64)) peptides all bound well to B*3501; however, the CTL response in individuals expressing this HILA allele was directed strongly and exclusively towards the 11-mer peptide. In contrast, EBV-exposed donors expressing HLA B*3503 showed no significant CTL response to these peptides because the single amino acid difference between B*3501 and B*3503 within the F pocket inhibited HLA binding by these peptides. The extraordinarily long 13-mer peptide was the target for the CTL response in individuals expressing B*3508, which differs from B*3501 at a single position within the D pocket (B*3501, 156 Leucine; B*3508, 156 Arginine). This minor difference was shown to enhance binding of the 13-mer peptide, presumably through a stabilizing interaction between the negatively charged glutamate at position 3 of the peptide and the positively charged arginine at HLA position 156. The 13-mer epitope defined in this study represents the longest class I-binding viral epitope identified to date as a minimal determinant. Furthermore, the potency of the response indicates that peptides of this length do not present a major structural barrier to CTL recognition.
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The underlying generic properties of {alpha}β TCRs that control MHC restriction remain largely unresolved. To investigate MHC restriction, we have examined the CTL response to a viral epitope that binds promiscuously to two human leukocyte Ags (HLAs) that differ by a single amino acid at position 156. Individuals expressing either HLA-B*3501 (156Leucine) or HLA-B*3508 (156Arginine) showed a potent CTL response to the 407HPVGEADYFEY417 epitope from EBV. Interestingly, the response was characterized by highly restricted TCR β-chain usage in both HLA-B*3501+ and HLA-B*3508+ individuals; however, this conserved TRBV9+ β-chain was associated with distinct TCR {alpha}-chains depending upon the HLA-B*35 allele expressed by the virus-exposed host. Functional assays confirmed that TCR {alpha}-chain usage determined the HLA restriction of the CTLs. Structural studies revealed significant differences in the mobility of the peptide when bound to HLA-B*3501 or HLA-B*3508. In HLA-B*3501, the bulged section of the peptide was disordered, whereas in HLA-B*3508 the bulged epitope adopted an ordered conformation. Collectively, these data demonstrate not only that mobile MHC-bound peptides can be highly immunogenic but can also stimulate an extremely biased TCR repertoire. In addition, TCR {alpha}-chain usage is shown to play a critical role in controlling MHC restriction between closely related allomorphs.
Combinatorial approach to multi-substituted 1,4-Benzodiazepines as novel non-peptide CCK-antagonists
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For the drug discovery process, a library of 168 multisubstituted 1,4-benzodiazepines were prepared by a 5-step solid phase combinatorial approach. Substituents were varied in the 3,5, 7 and 8-position on the benzodiazepine scaffold. The combinatorial library was evaluated in a CCK radiolabelled binding assay and CCKA (alimentary) and CCKB (brain) selective lead structures were discovered. The template of CCKA selective 1,4-benzodiazepin-2-ones bearing the tryptophan moiety was chemically modified by selective alkylation and acylation reactions. These studies provided a series of Asperlicin naturally analogues. The fully optimised Asperlicin related compound possessed a similar CCKA activity as the natural occuring compound. 3-Alkylated 1,4-benzodiazepines with selectivity towards the CCKB receptor subtype were optimised on A) the lipophilic side chain and B) the 2-aminophenyl-ketone moiety, together with some stereochemical changes. A C3 unit in the 3-position of 1,4-benzodiazepines possessed a CCKB activity within the nanomolar range. Further SAR optimisation on the N1-position by selective alkylation resulted in an improved CCKB binding with potentially decreased activity on the GABAA/benzodiazepine receptor complex. The in vivo studies revealed two N1-alkylated compounds containing unsaturated alkyl groups with anxiolytic properties. Alternative chemical approaches have been developed, including a route that is suitable for scale up of the desired target molecule in order to provide sufficient quantities for further in vivo evaluation.
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We have investigated how optimal coding for neural systems changes with the time available for decoding. Optimization was in terms of maximizing information transmission. We have estimated the parameters for Poisson neurons that optimize Shannon transinformation with the assumption of rate coding. We observed a hierarchy of phase transitions from binary coding, for small decoding times, toward discrete (M-ary) coding with two, three and more quantization levels for larger decoding times. We postulate that the presence of subpopulations with specific neural characteristics could be a signiture of an optimal population coding scheme and we use the mammalian auditory system as an example.
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2000 Mathematics Subject Classification: Primary 30C45, 26A33; Secondary 33C15
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Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions.
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2000 Mathematics Subject Classification: 60J80