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。

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

Tree boosting is a highly effective and widely used machine learning method. In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges. We propose a novel sparsity-aware algorithm for sparse data and weighted quantile sketch for approximate tree learning. More importantly, we provide insights on cache access patterns, data compression and sharding to build a scalable tree boosting system. By combining these insights, XGBoost scales beyond billions of examples using far fewer resources than existing systems.

/pdf/xgboost-a-scalable-tree-boosting-system-48ocu6x4c7.pdf

XGBoost: A Scalable Tree Boosting System

In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/. To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine -- the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.

/pdf/the-anatomy-of-a-large-scale-hypertextual-web-search-engine-496poj789d.pdf

The anatomy of a large-scale hypertextual Web search engine

The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.

The PageRank Citation Ranking : Bringing Order to the Web

Disclosed herein are polynucleotides encoding multi-epitope polypeptides and assemblies thereof, and their use for treating or limiting Toxoplasma gondii infection.

Toxoplasma gondii vaccines and their use

: Modern breast cancer therapies utilize non-specific approaches to kill or remove cancerous cells, inflicting significant collateral damage to healthy cells. In response to the need for highly targeted detection and destruction of cancerous cells, we propose to implement multi-input genetic circuits that act as cell state classifiers based on mRNA or microRNA expression profiling. The mRNA sensing project is focused on the MCF-7 breast adenocarcinoma cell line. MCF-7 cells overexpress Gata3, NPY1R and TFF1 mRNA relative to healthy cells. Based on our bioinformatics analysis, taking into account the three biomarkers allows for dramatically improved specificity in comparison to targeting single genes. We therefore design a three-input AND gate that triggers a response only when all three biomarkers are expressed above a defined threshold. In second approach we implement transcriptional/post-transcriptional regulatory circuit that senses expression levels of a customizable set of endogenous microRNAs and computes whether to trigger a response if the expression levels match a pre-determined profile of interest. We have created a circuit that computes a complex abstract logic (miR1 AND miR2+3 AND NOT miR4 AND NOTmiR5 AND NOT miR6) and selectively triggers output response in HeLa but not in other cells.

An RNAi-Enhanced Logic Circuit for Cancer Specific Detection and Destruction

Provided herein are genetic circuits and cell state classifiers for detecting the microRNA profile of a cell. In some embodiments, the cell state classifiers described herein utilize an endoribonuclease and a self-amplifying RNA molecule for controlling the expression of an output molecule. In some embodiments, the cell state classifiers described herein are encoded on a single RNA transcript, which is then processed to produce individual genetic circuits that function independently. The genetic circuits and cell state classifiers described herein may be used in various applications (e.g., therapeutic or diagnostic applications).

Rna-based regulatory technologies for mirna sensors

The disclosure provides novel large serine recombinases and their respective recognition sites, as well as libraries of orthogonal recombinase recognition sites. Uses of the large serine recombinases, recognition sites, and libraries of orthogonal recombinase recognition sites also are provided.

Recombinases and target sequences

The disclosure provides methods for an in vitro evolution technique to identify and characterize mutations in the non- structural genes of an alphavirus replicon that increase the strength and persistence of expression of the replicon genome. Also provided herein are in vivo methods for administering to an animal model a mutated alphavirus replicon that codes for a gene of experimental or therapeutic interest in the subgenome of the alphavirus replicon. The mutations identified herein improve the therapeutic potential of self-replicating RNA, which may have implications for cancer immunotherapy and beyond, e.g., for vaccination or gene therapy.

Ron Weiss

Papers

Toxoplasma gondii vaccines and their use

An RNAi-Enhanced Logic Circuit for Cancer Specific Detection and Destruction

Rna-based regulatory technologies for mirna sensors

Recombinases and target sequences

Methods for in vitro evolution of rna replicons