A fuzzy approach to image analysis in HLA typing using oligonucleotide microarrays

被引:2
作者
Ferrara, GB
Delfino, L
Masulli, F
Rovetta, S
Sensi, R
机构
[1] Univ Pisa, INFM, I-16146 Genoa, Italy
[2] IST, Ist Nazl Ric Canc, I-16132 Genoa, Italy
[3] Univ Pisa, Dipartimento Informat, I-56125 Pisa, Italy
[4] Univ Genoa, Dipartimento Informat & Sci Informaz, I-16146 Genoa, Italy
关键词
HLA typing; oligonucleotide microarrays; probe hybridization labelling; fuzzy modeling; fuzzy systems;
D O I
10.1016/j.fss.2004.10.013
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The human leukocyte antigen (HLA) region is a part of genome which spans over 4 Mbases of DNA. The HLA system is strongly connected to immunological response and its compatibility between tissues is critical in transplantation. We have developed an application of oligonucleotide microarrays to HLA typing. In this paper, we present a method based on a fuzzy system which interactively supports the user in analyzing the hybridization results, speeding-up the decision process moving from raw array data obtained from the scanner to their interpretation (genotyping). The two-level procedure starts with evaluation of spot activity, then it estimates probe hybridization levels from activity levels. The method is designed for being readily usable by the biologist, by adopting fuzzy linguistic variables which are familiar to the user and by featuring a standard and complete graphical interface. (c) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:37 / 48
页数:12
相关论文
共 24 条
  • [1] Asymptotic statistical theory of overtraining and cross-validation
    Amari, S
    Murata, N
    Muller, KR
    Finke, M
    Yang, HH
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1997, 8 (05): : 985 - 996
  • [2] [Anonymous], SOFT COMPUTING APPRO
  • [3] Casalino F, 1998, INTELL AUTOM SOFT CO, V4, P73
  • [4] Microarrays: their origins and applications
    Ekins, R
    Chu, FW
    [J]. TRENDS IN BIOTECHNOLOGY, 1999, 17 (06) : 217 - 218
  • [5] Gerlach JA, 2002, ARCH PATHOL LAB MED, V126, P281
  • [6] Guo Z, 1999, Rev Immunogenet, V1, P220
  • [7] ANFIS - ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEM
    JANG, JSR
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1993, 23 (03): : 665 - 685
  • [8] JOU CC, 1993, 1993 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-3, P1028, DOI 10.1109/ICNN.1993.298699
  • [9] KATZER M, 2002, BREW BIOINF RES ED W
  • [10] KIM HM, 1995, IEEE T FUZZY SYST, V3, P158, DOI 10.1109/91.388171