How to pronounce molecular in English

This( molecular hydrogen) is just like the icing on the cake, now, you see the chemical energy source that microbes could use. The only thing we haven't seen is phosphorus and sulfur, and that's probably because they were in small enough quantities that we didn't see them. We have to go back and look and search for signs of life as well.

It's not whether you have pancreatic cancer, or colon cancer or lung cancer that's going to be important to the treating clinician, what's going to be important to the treating clinician is what's wrong with your tumor at a molecular level.

Coussens said. FOLLOW US ON FACEBOOK FOR MORE FOX LIFESTYLE NEWS One scientist that has helped change the landscape for the treatment of cancer is molecular cell biologist Dr. Tony Hunter, Salk Institute for Biological Studies, who discovered a cellular process that has helped produce 26 approved drugs for cancer treatment. Were interested in how cancer cells differ from normal cells and in particular how the internal signaling pathways differ and how potentially one can exploit differences to develop new types of therapy.

You can see a molecular echo of what’s left behind.

This is the new molecular medicine.

Having our hands on this gene allows us to develop molecular breeding approaches to creating bespoke poppy varieties that make different compounds.

The irony of individualized treatment for one patient is that we have to manage billions of bits of information from thousands of others, the selection of a precise cancer therapy based on a patient's molecular profile requires computer-assisted analysis of enormous molecular, clinical, patient history, and pharmacological datasets that often come from very disparate and heterogeneous data sources.

We really want to make this a realistic thing, but we understand that it is not the easiest thing in the world to do, with today's molecular technology, it is quite possible.

Basics of Macro-systems' Behavior Prediction 1 .The Macro-systems with their sometimes stochastic behavior may be (good) indicators of the dispersal of information from a holistic standpoint as well as [to be discussed later on] from a regionally molecular anisotropic zone. 2. The data scattering as for systems with quasi-vector behavior on liquids, on gases, and amongst solids, when observed from an epi-phenomenological perspective versus a phenomenological one, can show that a number of classical views on mechanistic behavior of Macro-systems may be substituted with some “machinic” view.¬ 3. The abandonment of the purely mechanistic view of interfacial forces and the adoption of thermodynamic and probabilistic concepts such as free energy and entropy have been two of the most important steps towards getting out of the worn-out mechanistic notions into more abstract conceptualization of information dispersal, working instead of causality. 4. Comparison also has to be made between hermeneutics of the notion of entropic forces within and without the framework of established thermodynamics. The very word “force” is itself a bit too collocated with entropy already. What we are after is to make it next of kin to ideas of data, information, topology of data, and mereology of stochasticity. 5. The physico-chemical potentiality inside a variety of equilibrium states can be used as a platform for anisotropic configurations whereby not only the entropy of confinement, but also the entropy of dispersal find their true meaning. 6. Within contexts of classical accumulation and energy-growth models, the verifiability of any anisotropic reversal is also demonstrable, if not by means of a set of axioms, at least by multiplicities of interfacial behavior in which experimental data find their mereotopological ratios one in the neighborhood of the other (considering first, for the sake of simplicity, our state spaces to be of metric nature). 7. Thus, there remains the reciprocity of interfacial tensions calculations where surface tension gives rise to internal polarization of those data systems by which we should like to derive either axiomatic or multiple manifoldic regionalization of PREDICTION. 8. This, with a number of Chaotic and Strange-Attractors modifications, can potentially be applied even to the whole matrix of the Universe. 9. Most of the literature on systems (information) entropy regard mesoscopic level as THE one with highest aptitude for (physicalistic) data analysis. However, there are clues to indicate that some of the main streams of structuration and dynamics are EITHER in common amongst microscopic, mesoscopic, and macroscopic systems OR holistic patterns of the said structurations and dynamics can be derived one from the other two. For example, we shall show later—in the course of the unfolding of present notions—that density functional theory (DFT) which has become the physicists’ methodology for describing solids’ electronic structure, can also be extended to other methods or systems. Few-atom systems can implicate the already explicated order of, say, biomolecules if rigorous analyses are carried out over the transition phases (translational data mappings). 10. The level of likelihood of information dispersal in any nano- and pico-systems with/without (full) attachment to and/or dependence upon chemical energy exchange, relates to dynamics of differentials of those multiplicities of tubing interconnector manifolds which potentially have the capacity to harness thermal energy. This spells that consumption of chemical energy does not necessarily always act against the infusion of energy. Here, delineation has to be made over the minutiae of the differences between Micro- and Macro-systems. Any movement of lines of demarcation throughout the said systems over the issue of (non-)interdependency of data mereotopology on chemical energy exchange, may be predicted if classical nucleation and growth theories give their place to an even more rigorous science of Differences. Repetition of (observation) of such Differences makes it possible to see through some of the most “macro” levels of systematicity [we have already run some simulations of micro-spaces’ state mappings for purposes of clarifying how many of the plasma macro jet streams inside stars or in the inter-galaxial space move. Even magneticity has turned out, with all due caution, to be comparable]. The above-said Differences actually refer to potentialities within lines of thermodynamic exchanges based upon anisotropy of information. Such exchanges nominate themselves as MO exchanges when “micro” but as some the most specific gravito-convectional currents in usages for astrology, earth science, and ecology. Thence, the science will be brought out of prognosing the detailed balance of mesoscopic (ir-)reversibility in terms of data neighborhoods connectivity. On any differentiable manifold with its own ring of universal differentiable functions, we may determine to have the “installing” of modules of Kähler spaces where demarcation could be represented by: d(a+b)=da+db, d(ab)=adb+bda, and: dλ=0(a,b∈A,λ∈k)d(a+b)=da+db,d(ab)=adb+bda,dλ=0(a,b∈A,λ∈k) Where any one module has the formalism: dbdb (b∈Ab∈A). All these having been said, again we have the problematics of still remaining within the realm of classic calculus. It is likely that for Macrosystems we may decide not to apply the classical version.

Corals are facing unprecedented declines due to climate change, motivating researchers to understand molecular basis of their thermal tolerance, how they complete their life cycle, and interactions with algae that live inside them, our ability to understand how specific genes contribute to these traits in corals is held back by the lack of methods to test how a particular gene functions in corals.