Project potential problems analysi

Plan the work carefully. At the beginning of an extended project, formally analyze the proposed program for possible hazards and consider the consequences of possible failures or errors. Ask a colleague to review the hazard analysis with you. Being too close to a subject often leads to overlooking potential problems. Unfortunately, even with the best plans, eventualities will exist which no one thinks of, and these are just the ones which may result in accidents. 

The important messages to remember from this chapter are to think carefully about the discovery experiment first. Put together a solid team with the skills necessary to accomplish the project. Think carefully about the question that is being asked Is it reasonable and achievable Plan the project well and listen to potential problems and challenges so that the question can be answered satisfactorily. Focus on the question being asked and do not get sidetracked until there is an answer to the initial question there is always an opportunity to investigate the data further after the question has been answered. Simplify each step in the biomarker discovery experiment as much as possible so that the data analysis results are as clear as possible. 

The X data matrix which contains all information describing the probe-target interactions can be analyzed by PCA [29, 30]. PCA is a multivariate projection method which allows one to extract the systematic information which is contained in the data matrix and to present it in a simplified form. The original number of variables is reduced to a few factors called principal components (PCs). The result of such an analysis can then be visualized by means of two informative plots which allow a straightforward interpretation of the problem. In this way, PCA provides an understanding of similarities and dissimilarities between the different protein binding sites with respect to their interaction with potential ligands. 

In this case one may use the symmetry of the Coulomb potential and apply the comparison theorem for the ground state wavefunction ir r) and the "reflected" function external potential t/i(r) = U(err). As comparison theorem one finds ir r) > Hellmann-Feynman force is oriented into E+, that is, its n-projection is positive. Practically the same discussion was used in [34] to prove the monotone nature of the adiabatic potential for the ground state of the one-electron diatomic molecule (in the absence of the internuclear repulsion term). This statement is also easily modified for the Dirichlet boundary value problem for some region 2. One may formally require the external potential U to be infinite out of 2 (for the analysis of this statement see [35]). 

In this chapter, new tools for exploratory data analysis are presented and combined with already well known techniques in the chemometrics field, such as projection models, score and loading plots. The shortcomings and potential pitfalls in the application of common tools are elucidated and illustrated with examples. Then, the new techniques are introduced to overcome these problems. 

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