Proteomics technology is progressing at an incredible rate and has been widely used in proteomics for its high reliability and efficiency.

 

Sennsichip Bioinformatics Analysis Platform can analyses several kinds of data sets derived from Mass spectrometry-based shotgun protomics、Surface-enhanced laser desorption/ionization (SELDI)、Matrix-assisted laser desorption/ionization (MALDI) and Isobaric tag for relative absolute quantitation(ITRAQ) technology. The analysis workflow is listed below:

Step one--Differential Expression proteins selection

Differential Expression (DE) peptides could be identified using t-test or ANOVE. High level proteins can match much more peptides than low level proteins. So we can select differential proteins(P<0.01). DE proteins would be separated into two groups of up-regulated gene group and down-regulated gene group according to each protein’s expression level.
    

Step two—Gene Ontology analysis

Gene Orthology (GO) analysis tools were performed to classify the DE proteins. The significance between DE proteins and GO node were identified using T-test. Based on P value <=0.05. Every DE protein could be mapping into a significant GO node.

Step three—Pathway analysis

By searching KEGG and BioCarta database, each differential expression (DE) proteins would be mapped into certain biochemical pathway. Statistical analysis (such as Fisher exact test) was performed to identify the significance between DE proteins and pathways.

 

 

Step four--Transcription Factor Analysis
The DE proteins are retrieved in Transcription Factor (TF) database for finding out whether these genes have certain TF binding site. If it does, the result suggests there exists certain relationships between TFs and DE proteins.

Step five--Protein Regulation Pathway Analysis

This analysis builds up the protein-protein interaction network based on the literature co-citation analysis and transcription factor binding analysis. In the example below, the upper figure suggests the yellow color enlighted proteins should be transcription factor. In the lower graph, the yellow color enlighted proteins represent they are key knots of proteins interaction network.

overview
Our from Fudan University and American Ph.D with experience in pharmaceutical design, bioinformatics services, biological software, and database development. The major of our products and services is covering the following fields: gene chip, protein chip, mass spectrumetry, and experiment design, data analysis, results validation of high-throughput sequencing, a multi-dimensional solutions including of modification of SCI paper.

We have constructed a professional bioinformatics service platform based on Matlab and R language. At Sensichip, we intend to integrate scientific research achievements of today’s bioinformatics, and technologies and products used by data analysis. Our platform provides a wide variety of professional services for gene expression profiling array, microRNA array, SNP array, Exon array, MeDIP-chip, Oligo chip, CGH array, protein array, cytokine array, and data analysis including mass spectrumetry, metabolismics and high-throughput sequencing.

We have achieved success to extend platform to text mining, database construction, biological analysis software development, based on java, perl, C++, and so on. At present, Sensichip has over 200 customers at home and aboard, published many SCI papers with a high impact factor, and participated application and implementation of much national fund.

Technical Innovation

＊ HDMD (Human Disease Microarray Database)
Storing and analyzing microarray data for complex human disease such as tumour and diabetes.

＊ PMBA (Plant Microarray Bioinformatics Analysis)
An integrated microarray analysis system for rice and Arabidopsis.

＊ MMCP (Multiple Methods for Class Prediction)

A software integrating ANN, SVM, PNN, PAM methods for class prediction using gene expression data.

＊ PlantQTL-GE
A database system for identifying candidate genes in rice and Arabidopsis by gene expression and QTL information
nstroduction
Genomics
Our major business:
microRNA analysis (including: routine analysis, three-dimensional structure prediction, the network building)
solexa sequencing experiments and analysis services (small RNA sequencing, mRNA sequencing, ChIP-Seq sequencing, RNA-Seq sequencing, whole-genome re-sequencing, bacterial whole-genome sequencing, DNA methylation sequencing).
Co-published papers:
· Chen Lei, et al., The role of microRNA expression pattern in human intrahepatic cholangiocarcinoma, Journal of Hepatology,2009,50(2):358-369,IF=6.642
· Ding JJ, et al., ES Cells Derived from Somatic Cloned and Fertilized Blastocysts are post-transcriptionally Indistinguishable: a MicroRNA and Protein Profiles Compariso, proteomics, 2009,9,1–11,IF=6.088
· Hu SJ, Ren G, Liu JL,et al,. MicroRNA expression and regulation in mouse uterus during embryo implantation, J Biol Chem. 2008 Aug 22;283(34).IF=5.6
· Guodong Li; Wenjuan Zhang; Huazong Zeng et al., Identification of new biomarkers for osteosarcoma early diagnosis from evidences of SELDI-TOF-MS and microarray,BMC cancer, 2009,9:150,IF=3.08

Proteomics
We are focus on:
DIGE-2D experiments and analysis
iTRAQ experiments and data analysis
MALDI-TOF-MS experiments and analysis
SELDI experiments and analysis,
Shortgun Protomics and so on.
Co-published papers:
· Ding JJ, et al., ES Cells Derived from Somatic Cloned and Fertilized Blastocysts are post-transcriptionally Indistinguishable: a MicroRNA and Protein Profiles Compariso, proteomics, 2009,9,1–11,IF=6.088
· Jinghui Guo et al.,Identification of Serum Biomarkers for pancreatic adenocarcinoma by Proteomic analysis .Cancer Science,2009.IF=3.47
· Guodong Li; Wenjuan Zhang; Huazong Zeng et al., Identification of new biomarkers for osteosarcoma early diagnosis from evidences of SELDI-TOF-MS and microarray,BMC cancer, 2009,9:150,IF=3.08

Metabolomics
We are focus on
LC-MS experiments and analysis
GC-MS experiments and analysis NMR experiments and analysis.
Co-published papers:
· Hao Wu, Ruyi Xue , Huazong Zeng, Xizhong Shen et al., Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry, Analytica Chimica Acta,IF=3.18
· Hao Wu, Huazong Zeng, Xizhong Shen et al., Metabolomic study for diagnostic model of oesophageal cancer using gas chromatography/mass spectrometry, Journal of Chromatography B, 877 (2009) 3111–3117 .IF=2.935

Microarray analysis
We are focus on:
Gene Chip analysis
MicroRNA Chip
methylation (cGp) microarray analysis
exon microarray analysis
Protein Chip analysis
SNP Chip analysis
antibody microarray analysis.
Co-published papers:
· Ding JJ, et al., ES Cells Derived from Somatic Cloned and Fertilized Blastocysts are post-transcriptionally Indistinguishable: a MicroRNA and Protein Profiles Compariso, proteomics, 2009,9,1–11,IF=6.088
· Guodong Li; Wenjuan Zhang; Huazong Zeng et al., Identification of new biomarkers for osteosarcoma early diagnosis from evidences of SELDI-TOF-MS and microarray,BMC cancer, 2009,9:150,IF=3.08

Literature mining
We are focus on:
Disease & Gene literature mining,
Gene & Gene literature mining
SNP mining literature
CpG literature mining.

Training
Let bioinformatics training come to you. Onsite training is ideal for groups of researcher or those who need customized instruction on bioinformatics analysis. To maximize productivity with the bioinformatics tools, instructors can tailor the curriculum with institute or industry-specific examples, and address challenges and process issues familiar to students from your organization.