Data Mining Practical Machine Learning Tools and Techniques

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

I read this book the same weekend that the Packers took on the Rams, and the experience of the latter event, obviously, colored my judgment. Although I abhor anything that smacks of being a handbook (like, \"How to Earn a Merit Badge in Neurosurgery\") because too many volumes in biomedical science already evince a boyscout-like approach, I must confess that parts of this volume are fast, scholarly, and significant, with certain reservations. I like parts of this well-illustrated book because Dr. Sj6strand, without so stating, develops certain subjects on technique in relation to the acquisition of judgment and sophistication. And this is important! So, given that the author (like all of us) is somewhat deficient in some areas, and biased in others, the book is still valuable if the uninitiated reader swallows it in a general fashion, realizing full well that what will be required from the reader is a modulation to fit his vision, propreception, adaptation and response, and the kind of problem he is undertaking. A major deficiency of this book is revealed by comparison of its use of physics and of chemistry to provide understanding and background for the application of high resolution electron microscopy to problems in biology. Since the volume is keyed to high resolution electron microscopy, which is a sophisticated form of structural analysis, but really morphology in a modern guise, the physical and mechanical background of The instrument and its ancillary tools are simply and well presented. The potential use of chemical or cytochemical information as it relates to biological fine structure , however, is quite deficient. I wonder when even sophisticated morphol-ogists will consider fixation a reaction and not a technique; only then will the fundamentals become self-evident and predictable and this sine qua flon will become less mystical. Staining reactions (the most inadequate chapter) ought to be something more than a technique to selectively enhance contrast of morphological elements; it ought to give the structural addresses of some of the chemical residents of cell components. Is it pertinent that auto-radiography gets singled out for more complete coverage than other significant aspects of cytochemistry by a high resolution microscopist, when it has a built-in minimal error of 1,000 A in standard practice? I don't mean to blind-side (in strict football terminology) Dr. Sj6strand's efforts for what is \"routinely used in our laboratory\"; what is done is usually well done. It's just that …

Methods in Enzymology.

Implicit Solvation Models: Equilibria, Structure, Spectra, and Dynamics.

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

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Computational Methods in Drug Discovery

The structure and shape of the polypeptide chains of proteins are determined by the hybridized states of the atomic orbitals in the molecular chain. The calculated s ratio in the sp n hybrid orbitals is computed from the fractal dimension D of the tertiary structures of 43 proteins selected to cover the five structural classes of protein molecules. A brief introduction to fractal theory is given in the text. It is demonstrated that the principles dictating the folding of the local and global backbone structures are well characterized in terms of the representation given by fractal theory. Comparison of the fractal character of protein molecules with that of the ideal Gaussian chain revealed several features of these principles. It is also shown that proteins in the β type structural class are distinguished quantitatively from those in other classes with this representation. They show a higher s ratio (0.32) in sp 2.20 hybrids, rather similar to planar sp 2 . Comparison of the proteins with a Gaussian chain is interpreted in terms of

/pdf/fractal-hybrid-orbitals-analysis-of-the-tertiary-structure-5b72zfvrh5.pdf

Fractal Hybrid Orbitals Analysis of the Tertiary Structure of Protein Molecules

Prediction of Caco-2 Cell Permeability Using Bilinear Indices and Multiple Linear Regression

Classification of stilbenoid compounds by entropy of artificial intelligence.

The periodic table of the elements (PTE) results essential to understand our nature and place in the whole of beings. The same happens with our food, drugs, materials, etc. A series of questions were asked to introduce PTE and provide answers. The ideas in PTE should be valued by the number of questions that they generate. The PTE was related to electron configurations. The emergence of elements (nucleosynthesis) in physics was explained. The PTE results essential to understand our nature and place in the whole of beings. The same happens with our food, drugs, materials, etc. Schwarz and Rich asked a series of questions (Qs) to introduce PTE and provided answers. The ideas on PTE should be valued by the number of questions that they generate. Q1. Why are the halogens and alkali metals among the first groups treated in chemistry courses? Q2. What is the physical origin of the periods' lengths? Q3. Why are the closed p6 shells of the inert gases more stable than other closed shells, viz. s2 and d10 of chemically active metals (of groups 2, 12 and 10)? Q4. Textbooks give the electron configuration of the transition elements as ns2(n – 1)dG–2 with a few exceptions (G is the number of valence electrons or group number in PTE and n, the main quantum number or period number). Why is transition-metal chemistry practically pure d-atomic orbital (AO) chemistry? Etcetera. A need exists to develop theoretical and experimental research on PTE to understand periodic properties and the periodic law.

/pdf/reflections-on-the-nature-of-the-periodic-table-of-the-4h6d410rg2.pdf

Reflections on the Nature of the Periodic Table of the Elements: Implications in Chemical Education

The interacting induced dipoles polarization model implemented in the program POLAR is used for the calculation of the molecular dipole-dipole polarizability . The method is tested with Sc1-Sc7, Sc12, Sc17, Sc74, C, C12, C60, C70, C82-fullerene, Sc@C60, Sc@C82, Sc2@C82, Sc3@C82, C1-C6, C10, C13, C16, C19, C22, C24, C42, C54, C84 and C96-graphite clusters. The polarizability is an important quantity for the identification of clusters with different numbers of atoms and even for the separation of isomers. The results for the polarizability are of the same order of magnitude as reference calculations performed with another program based on the same formulation. The bulk limit for the polarizability is estimated from the Clausius-Mossotti relationship. The polarizability trend for these clusters as a function of size is different from what one might have expected. The clusters are more polarizable than one might have inferred from the bulk. Previous theoretical work has yielded the same trend for small Sin, Gen and GanAsm clusters. However, previous experimental work has yielded the opposite trend for larger Sin, GanAsm and GenTem clusters. At present, the origin of this difference is problematic. One might argue that smaller clusters need not behave like those of intermediate size. The high polarizability of small clusters is attributed to dangling bonds at the surface of the cluster, which resembles a metallic cluster.

http://iopscience.iop.org/article/10.1088/0957-4484/13/3/338/pdf

Francisco Torrens

Papers

Fractal Hybrid Orbitals Analysis of the Tertiary Structure of Protein Molecules

Prediction of Caco-2 Cell Permeability Using Bilinear Indices and Multiple Linear Regression

Classification of stilbenoid compounds by entropy of artificial intelligence.

Reflections on the Nature of the Periodic Table of the Elements: Implications in Chemical Education

Molecular polarizability of Scn, Cn and endohedral Scn@Cm clusters