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According to the interpretation of Systems Biology as the ability to obtain, integrate and analyze complex data sets from multiple experimental sources using interdisciplinary tools, some typical technology platforms are phenomics, organismal variation in phenotype as it changes during its life span; genomics, organismal deoxyribonucleic acid (DNA) sequence, including intra-organismal cell specific variation. (i.e., telomere length variation); epigenomics/epigenetics, organismal and corresponding cell specific transcriptomic regulating factors not empirically coded in the genomic sequence. (i.e., DNA methylation, Histone acetylation and deacetylation, etc.); transcriptomics, organismal, tissue or whole cell gene expression measurements by DNA microarrays or serial analysis of gene expression; interferomics, organismal, tissue, or cell-level transcript correcting factors (i.e., RNA interference), proteomics, organismal, tissue, or cell level measurements of proteins and peptides via two-dimensional gel electrophoresis, mass spectrometry or multi-dimensional protein identification techniques (advanced HPLC systems coupled with mass spectrometry). Sub disciplines include phosphoproteomics, glycoproteomics and other methods to detect chemically modified proteins; metabolomics, measurements of small molecules known as metabolites in the system at the organismal, cell, or tissue level; glycomics, organismal, tissue, or cell-level measurements of carbohydrates;  lipidomics, organismal, tissue, or cell level measurements of lipids.

According to the interpretation of Systems Biology as the ability to obtain, integrate and analyze complex data sets from multiple experimental sources using interdisciplinary tools, some typical technology platforms are phenomics, organismal variation in phenotype as it changes during its life span; genomics, organismal deoxyribonucleic acid (DNA) sequence, including intra-organismal cell specific variation. (i.e., telomere length variation); epigenomics/epigenetics, organismal and corresponding cell specific transcriptomic regulating factors not empirically coded in the genomic sequence. (i.e., DNA methylation, Histone acetylation and deacetylation, etc.); transcriptomics, organismal, tissue or whole cell gene expression measurements by DNA microarrays or serial analysis of gene expression; interferomics, organismal, tissue, or cell-level transcript correcting factors (i.e., RNA interference), proteomics, organismal, tissue, or cell level measurements of proteins and peptides via two-dimensional gel electrophoresis, mass spectrometry or multi-dimensional protein identification techniques (advanced HPLC systems coupled with mass spectrometry). Sub disciplines include phosphoproteomics, glycoproteomics and other methods to detect chemically modified proteins; metabolomics, measurements of small molecules known as metabolites in the system at the organismal, cell, or tissue level; glycomics, organismal, tissue, or cell-level measurements of carbohydrates;  lipidomics, organismal, tissue, or cell level measurements of lipids.

根据系统生物学的解释，即利用跨学科工具从多个实验来源获取、整合和分析复杂数据集的能力，一些典型的技术平台包括表型学、生物表型在其生命周期内发生变化时的变异、基因组学、生物脱氧核糖核酸序列，包括生物内部细胞特异性变异。表观基因组学/表观遗传学、有机体和相应的细胞特异性转录调控因子，这些因子没有经验性地编码在基因组序列中。DNA 甲基化、组蛋白乙酰化和脱乙酰化等。) ; 转录组、生物组织、组织或整个细胞的基因表达测量，通过 DNA 微阵列或基因表达的系列分析; 干扰物、生物组织、组织或细胞水平的转录校正因子(即 RNA干扰) ; 蛋白质组学、生物组织、组织或细胞水平的蛋白质和多肽测量，通过二维凝胶电泳、质谱法或多维蛋白质识别技术(先进的高效液相色谱系统加上质谱法)。子学科包括磷酸蛋白质组学、糖蛋白质组学和其他检测化学修饰蛋白质的方法; 代谢组学，测量有机体、细胞或组织水平系统中被称为代谢物的小分子; 糖组学、有机体、组织或细胞水平的碳水化合物测量; 脂质组学、有机体、组织或细胞水平的脂质测量。

系统生物学具有利用跨学科工具从多个实验来源获取、整合和分析复杂数据集的能力，一些典型的技术平台包括：表型组学，即生物表型在其生命周期内的变化；基因组学，即生物脱氧核糖核酸序列、包括生物内部细胞特异性变异（例如端粒长度变化）；表观基因组学或表观遗传学，生命体和相应的细胞特异性转录调控因子没有经验性地编码在基因组序列中（例如 DNA 甲基化、组蛋白乙酰化和脱乙酰化等)；转录组学，通过 DNA 微阵列或基因表达的系列分析来测量生物体、组织或整个细胞的基因表达; 干扰素组学，即生物体、组织或细胞水平的转录校正因子（例如RNA干扰) ； 蛋白质组学，通过二维凝胶电泳、质谱法或多维蛋白质识别技术(先进的高效液相色谱系统加上质谱法)，进行生物体、组织或细胞水平的蛋白质和多肽测量。子学科包括磷酸蛋白质组学、糖蛋白质组学和其他检测化学修饰蛋白质的方法; 代谢组学，测量有机体、细胞或组织水平系统中被称为代谢物的小分子; 糖组学，有机体、组织或细胞水平的碳水化合物测量; 脂质组学，有机体、组织或细胞水平的脂质测量。