Mitosis—From Molecules to Machine
نویسندگان
چکیده
منابع مشابه
Spermatozoa Molecules in Relation to Bulls Fertility
Bull fertility may be defined as the process by which spermatozoa fertilize and activate the ovum and then support embryonic development. Bull fertility is a complex trait having relatively low heritability and plays a vital role for efficient production and reproduction of bovine. Various mechanisms involved in regulating bull fertility associated phenotype and reliable biomarkers are poorly d...
متن کاملApplication to Adaptive Control to Synchronous Machine Excitation
Self-tuning adaptive control technique has the advantage of being able to track the system operating conditions so that satisfactory control action can always be produced. Self-tuning algorithms can be implemented easily. Because the power systems are usually time varying non-linear systems and their parameters vary, adaptive controllers are very suitable for power systems. Characteristics of a...
متن کاملMachine learning unifies the modeling of materials and molecules Albert
Scientific Computing Department, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Oxfordshire OX11 0QX, UK. National Center for Computational Design and Discovery of Novel Materials (MARVEL), Lausanne, Switzerland. Laboratory of Computational Science and Modelling, Institute of Materials, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. Department of Ch...
متن کاملTransferable Atomic Multipole Machine Learning Models for Small Organic Molecules.
Accurate representation of the molecular electrostatic potential, which is often expanded in distributed multipole moments, is crucial for an efficient evaluation of intermolecular interactions. Here we introduce a machine learning model for multipole coefficients of atom types H, C, O, N, S, F, and Cl in any molecular conformation. The model is trained on quantum-chemical results for atoms in ...
متن کاملMachine learning unifies the modeling of materials and molecules
Determining the stability of molecules and condensed phases is the cornerstone of atomistic modeling, underpinning our understanding of chemical and materials properties and transformations. We show that a machine-learning model, based on a local description of chemical environments and Bayesian statistical learning, provides a unified framework to predict atomic-scale properties. It captures t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: American Zoologist
سال: 1989
ISSN: 0003-1569
DOI: 10.1093/icb/29.2.523