Cosmin Lazar

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A plenitude of feature selection (FS) methods is available in the literature, most of them rising as a need to analyze data of very high dimension, usually hundreds or thousands of variables. Such data sets are now available in various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics. As a general accepted(More)
Genomic data integration is a key goal to be achieved towards large-scale genomic data analysis. This process is very challenging due to the diverse sources of information resulting from genomics experiments. In this work, we review methods designed to combine genomic data recorded from microarray gene expression (MAGE) experiments. It has been acknowledged(More)
An increasing amount of microarray gene expression data sets is available through public repositories. Their huge potential in making new findings is yet to be unlocked by making them available for large-scale analysis. In order to do so it is essential that independent studies designed for similar biological problems can be integrated, so that new insights(More)
Photosynthesis has shaped atmospheric and ocean chemistries and probably changed the climate as well, as oxygen is released from water as part of the photosynthetic process. In photosynthetic eukaryotes, this process occurs in the chloroplast, an organelle containing the most abundant biological membrane, the thylakoids. The thylakoids of plants and some(More)
With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools(More)
Microarray technology has become an integral part of biomedical research and increasing amounts of datasets become available through public repositories. However, re-use of these datasets is severely hindered by unstructured, missing or incorrect biological samples information; as well as the wide variety of preprocessing methods in use. The inSilicoDb(More)
An acceleration of differentiation at the expense of proliferation is observed in our previous publications and in the literature after exposure of various biological models to low frequency and low-amplitude electric and electromagnetic fields. This observation is related with a significant modification of genes expression. We observed and compared over(More)
Genomics datasets are increasingly useful for gaining biomedical insights, with adoption in the clinic underway. However, multiple hurdles related to data management stand in the way of their efficient large-scale utilization. The solution proposed is a web-based data storage hub. Having clear focus, flexibility and adaptability, InSilico DB seamlessly(More)
The clustering capabilities of the Non Negative Matrix Factorization algorithm is studied. The basis images are considered like the membership degree of the data to a particular class. A hard clustering algorithm is easily derived based on these images. This algorithm is applied on a multivariate image to perform image segmentation. The results are compared(More)
Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug(More)