Richard E. Green

Bio: Richard E. Green is an academic researcher from University of California, Santa Cruz. The author has contributed to research in topics: Genome & Genomics. The author has an hindex of 60, co-authored 159 publications receiving 34888 citations. Previous affiliations of Richard E. Green include Kitt Peak National Observatory & University of California.

The Demography of massive dark objects in galaxy centers

Abstract: We construct dynamical models for a sample of 36 nearby galaxies with Hubble Space Telescope (HST) photometry and ground-based kinematics. The models assume that each galaxy is axisymmetric, with a two-integral distribution function, arbitrary inclination angle, a position-independent stellar mass-to-light ratio , and a central massive dark object (MDO) of arbitrary mass M•. They provide acceptable fits to 32 of the galaxies for some value of M• and ; the four galaxies that cannot be fitted have kinematically decoupled cores. The mass-to-light ratios inferred for the 32 well-fitted galaxies are consistent with the fundamental-plane correlation ∝ L0.2, where L is galaxy luminosity. In all but six galaxies the models require at the 95% confidence level an MDO of mass M• ~ 0.006Mbulge ≡ 0.006L. Five of the six galaxies consistent with M• = 0 are also consistent with this correlation. The other (NGC 7332) has a much stronger upper limit on M•. We predict the second-moment profiles that should be observed at HST resolution for the 32 galaxies that our models describe well. We consider various parameterizations for the probability distribution describing the correlation of the masses of these MDOs with other galaxy properties. One of the best models can be summarized thus: a fraction f 0.97 of early-type galaxies have MDOs, whose masses are well described by a Gaussian distribution in log (M•/Mbulge) of mean -2.28 and standard deviation ~0.51. There is also marginal evidence that M• is distributed differently for core and power law galaxies, with core galaxies having a somewhat steeper dependence on Mbulge.

A Draft Sequence of the Neandertal Genome

Abstract: Neandertals, the closest evolutionary relatives of present-day humans, lived in large parts of Europe and western Asia before disappearing 30,000 years ago. We present a draft sequence of the Neandertal genome composed of more than 4 billion nucleotides from three individuals. Comparisons of the Neandertal genome to the genomes of five present-day humans from different parts of the world identify a number of genomic regions that may have been affected by positive selection in ancestral modern humans, including genes involved in metabolism and in cognitive and skeletal development. We show that Neandertals shared more genetic variants with present-day humans in Eurasia than with present-day humans in sub-Saharan Africa, suggesting that gene flow from Neandertals into the ancestors of non-Africans occurred before the divergence of Eurasian groups from each other.

The Demography of Massive Dark Objects in Galaxy Centres

Abstract: We construct dynamical models for a sample of 36 nearby galaxies with Hubble Space Telescope photometry and ground-based kinematics. The models assume that each galaxy is axisymmetric, with a two-integral distribution function, arbitrary inclination angle, a position-independent stellar mass-to-light ratio Upsilon, and a central massive dark object (MDO) of arbitrary mass M_bh. They provide acceptable fits to 32 of the galaxies for some value of M_bh and Upsilon; the four galaxies that cannot be fit have kinematically decoupled cores. The mass-to-light ratios inferred for the 32 well-fit galaxies are consistent with the fundamental plane correlation Upsilon \propto L^0.2, where L is galaxy luminosity. In all but six galaxies the models require at the 95% confidence level an MDO of mass M_bh ~ 0.006 M_bulge = 0.006 Upsilon L. Five of the six galaxies consistent with M_bh=0 are also consistent with this correlation. The other (NGC 7332) has a much stronger upper limit on M_bh. We consider various parameterizations for the probability distribution describing the correlation of the masses of these MDOs with other galaxy properties. One of the best models can be summarized thus: a fraction f ~0.97 of galaxies have MDOs, whose masses are well described by a Gaussian distribution in log (M_bh/M_bulge) of mean -2.27 and width ~0.07.

The Transcriptional Landscape of the Mammalian Genome

Abstract: This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.

Abstract: The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space. AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors. The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

Abstract: High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

Abstract: Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.