@article {21479216,
	title = {Analysis of normal-tumour tissue interaction in tumours: prediction of prostate cancer features from the molecular profile of adjacent normal cells.},
	journal = {PloS one},
	volume = {6},
	year = {2011},
	month = {2011},
	pages = {e16492},
	abstract = {<p>Statistical modelling, in combination with genome-wide expression profiling techniques, has demonstrated that the molecular state of the tumour is sufficient to infer its pathological state. These studies have been extremely important in diagnostics and have contributed to improving our understanding of tumour biology. However, their importance in in-depth understanding of cancer patho-physiology may be limited since they do not explicitly take into consideration the fundamental role of the tissue microenvironment in specifying tumour physiology. Because of the importance of normal cells in shaping the tissue microenvironment we formulate the hypothesis that molecular components of the profile of normal epithelial cells adjacent the tumour are predictive of tumour physiology. We addressed this hypothesis by developing statistical models that link gene expression profiles representing the molecular state of adjacent normal epithelial cells to tumour features in prostate cancer. Furthermore, network analysis showed that predictive genes are linked to the activity of important secreted factors, which have the potential to influence tumor biology, such as IL1, IGF1, PDGF BB, AGT, and TGF\&beta;.</p>},
	author = {Trevino, Victor and Tadesse, Mahlet G and Vannucci, Marina and Fatima Al-Shahrour and Antczak, Philipp and Durant, Sarah and Bikfalvi, Andreas and Dopazo, Joaquin and Campbell, Moray J and Falciani, Francesco}
}
@article {17570147,
	title = {The AnnoLite and AnnoLyze programs for comparative annotation of protein structures},
	journal = {BMC Bioinformatics},
	volume = {8 Suppl 4},
	year = {2007},
	note = {Marti-Renom, Marc A Rossi, Andrea Al-Shahrour, Fatima Davis, Fred P Pieper, Ursula Dopazo, Joaquin Sali, Andrej Research Support, Non-U.S. Gov{\textquoteright}t England BMC bioinformatics BMC Bioinformatics. 2007 May 22;8 Suppl 4:S4.},
	pages = {S4},
	abstract = {BACKGROUND: Advances in structural biology, including structural genomics, have resulted in a rapid increase in the number of experimentally determined protein structures. However, about half of the structures deposited by the structural genomics consortia have little or no information about their biological function. Therefore, there is a need for tools for automatically and comprehensively annotating the function of protein structures. We aim to provide such tools by applying comparative protein structure annotation that relies on detectable relationships between protein structures to transfer functional annotations. Here we introduce two programs, AnnoLite and AnnoLyze, which use the structural alignments deposited in the DBAli database. DESCRIPTION: AnnoLite predicts the SCOP, CATH, EC, InterPro, PfamA, and GO terms with an average sensitivity of  90\% and average precision of  80\%. AnnoLyze predicts ligand binding site and domain interaction patches with an average sensitivity of  70\% and average precision of  30\%, correctly localizing binding sites for small molecules in  95\% of its predictions. CONCLUSION: The AnnoLite and AnnoLyze programs for comparative annotation of protein structures can reliably and automatically annotate new protein structures. The programs are fully accessible via the Internet as part of the DBAli suite of tools at http://salilab.org/DBAli/.},
	keywords = {*Algorithms Amino Acid Sequence Confidence Intervals Data Interpretation, Amino Acid *Software Structure-Activity Relationship, Protein Information Storage and Retrieval/methods Molecular Sequence Data Proteins/*chemistry/classification/*metabolism Sensitivity and Specificity Sequence Alignment/*methods Sequence Analysis, Protein/*methods Sequence Homology, Statistical *Databases},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17570147},
	author = {M. A. Marti-Renom and Rossi, A. and Fatima Al-Shahrour and Davis, F. P. and Pieper, U. and Dopazo, J. and Sali, A.}
}
