Institution
Stanford University
Education•Stanford, California, United States•
About: Stanford University is a education organization based out in Stanford, California, United States. It is known for research contribution in the topics: Population & Transplantation. The organization has 125751 authors who have published 320347 publications receiving 21892059 citations. The organization is also known as: Leland Stanford Junior University & University of Stanford.
Topics: Population, Transplantation, Medicine, Cancer, Gene
Papers published on a yearly basis
Papers
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TL;DR: Alkylations with Phenols, Nitrogen Nucleophiles in AAA Total Synthesis, and Considerations for Enantioselective Allylic Alkylation are presented.
Abstract: A. Primary Alcohols as Nucleophiles 2931 B. Carboxylates as Nucleophiles 2931 C. Alkylations with Phenols 2932 IV. Nitrogen Nucleophiles in AAA Total Synthesis 2935 A. Alkylamines as Nucleophiles 2935 B. Azides as a Nucleophile 2936 C. Sulfonamide Nucleophiles 2937 D. Imide Nucleophiles 2938 E. Heterocyclic Amine Nucleophiles 2940 V. Sulfur Nucleophiles 2941 VI. Summary and Conclusions 2941 VII. Acknowledgment 2941 VIII. References 2942 I. Considerations for Enantioselective Allylic Alkylation
2,230 citations
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TL;DR: A psychological space is established for any set of stimuli by determining metric distances between the stimuli such that the probability that a response learned to any stimulus will generalize to any other is an invariant monotonic function of the distance between them.
Abstract: A psychological space is established for any set of stimuli by determining metric distances between the stimuli such that the probability that a response learned to any stimulus will generalize to any other is an invariant monotonic function of the distance between them. To a good approximation, this probability of generalization (i) decays exponentially with this distance, and (ii) does so in accordance with one of two metrics, depending on the relation between the dimensions along which the stimuli vary. These empirical regularities are mathematically derivable from universal principles of natural kinds and probabilistic geometry that may, through evolutionary internalization, tend to govern the behaviors of all sentient organisms.
2,225 citations
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TL;DR: A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function.
Abstract: A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
2,225 citations
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TL;DR: In this article, a nonparametric multiple regression (NMM) method is presented, which models the regression surface as a sum of general smooth functions of linear combinations of the predictor variables in an iterative manner.
Abstract: A new method for nonparametric multiple regression is presented. The procedure models the regression surface as a sum of general smooth functions of linear combinations of the predictor variables in an iterative manner. It is more general than standard stepwise and stagewise regression procedures, does not require the definition of a metric in the predictor space, and lends itself to graphical interpretation.
2,224 citations
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TL;DR: The ability of transition metal complexes to preorganize π-electron systems serves as the basis both of simple additions usually accompanied by subsequent hydrogen shifts and of cycloadditions as mentioned in this paper.
Abstract: Enhancing the efficiency of the synthesis of complex organic products constitutes one of the most exciting challenges to the synthetic chemist. Increasing the catalogue of reactions that are simple additions or that minimize waste production is the necessary first step. Transition metal complexes, which can be tunable both electronically and sterically by varying the metal and/or ligands, are a focal point for such invention. Except for catalytic hydrogenation, such methods have been rare in complex synthesis and virtually unknown for CC bond formation until the advent of cross-coupling reactions. These complexes may orchestrate a variety of CC bond-forming processes, important for creation of the basic skeleton of the organic structure. Their ability to insert into CH bonds primes a number of different types of additions to relatively nonpolar π-electron systems. Besides imparting selectivity, they make feasible reactions that uncatalyzed were previously unknown. The ability of these complexes to preorganize π-electron systems serves as the basis both of simple additions usually accompanied by subsequent hydrogen shifts and of cycloadditions. The ability to generate “reactive” intermediates under mild conditions also provides prospects for new types of CC bond-forming reactions. While the examples reveal a diverse array of successes, the opportunities for new invention are vast and largely untapped.
2,223 citations
Authors
Showing all 127468 results
Name | H-index | Papers | Citations |
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Eric S. Lander | 301 | 826 | 525976 |
George M. Whitesides | 240 | 1739 | 269833 |
Yi Cui | 220 | 1015 | 199725 |
Yi Chen | 217 | 4342 | 293080 |
David Miller | 203 | 2573 | 204840 |
David Baltimore | 203 | 876 | 162955 |
Edward Witten | 202 | 602 | 204199 |
Irving L. Weissman | 201 | 1141 | 172504 |
Hongjie Dai | 197 | 570 | 182579 |
Robert M. Califf | 196 | 1561 | 167961 |
Frank E. Speizer | 193 | 636 | 135891 |
Thomas C. Südhof | 191 | 653 | 118007 |
Gad Getz | 189 | 520 | 247560 |
Mark Hallett | 186 | 1170 | 123741 |
John P. A. Ioannidis | 185 | 1311 | 193612 |