正用着的服务器在打开Netbean的时候报磁盘空间不足。 因为这台机器一直是自己在用，于是登陆root用户，du -sh /home/* 想看看最近有没有人其他人在

Big data is everywhere, and its influence and practical omnipresence across multiple industries will just continue to grow. For life scientists with expertise and an interest in bioinformatics, computer science, statistics, and related skill sets, the job outlook couldn’t be rosier. Big pharma, biotech, and software companies are clamoring to hire professionals with experience in bioinformatics and the identification, compilation, analysis, and visualization of huge amounts of biological and health care information. With the rapid development of new tools to make sense of life science research and outcomes, spurred by innovative research in bioinformatics itself, scientists who are entranced by data can pursue more career options than ever before. By Alaina G. Levine

Today’s bioinformaticists are in for a real treat. With a seemingly endless stream of biological data being generated across sectors, there is high demand for talented, experienced professionals at the crossroads of biology, statistics, and computer science. Scientists who can analyze large amounts of information and present it in a clear manner to decisionmakers are finding the sky is the limit in terms of jobs and career pathways, especially in the big pharma and biotech sectors.

“It’s a fun place to be and an exciting time to be in big data,” remarks Sriram Mohan, professor of computer and software engineering at Rose-Hulman Institute of Technology, who is spending his sabbatical developing bioinformatics software for Avalon Consulting, a data management firm.

And what an immense amount of data it is, due in part to a paradigm shift in the field, from data generation to data analysis, says W. Jim Zheng, associate professor in the School of Biomedical Informatics at The University of Texas Health Science Center at Houston. Now, with so much data being produced because of easier and more cost-effective tools, there is an even greater need for specialists who can make sense of the mountains of information in such a way that is meaningful for scientists and clinicians, and ultimately beneficial to customers and patients.

The increase in job opportunities is also being driven by a change in how bioinformatics is perceived in industry and academia. Previously, “scientists and companies used to look at bioinformatics as a tool,” says Wim Van Criekinge, a professor of bioinformatics at Ghent University in Belgium and chief scientific officer at MDxHealth, a company developing epigenetics-based cancer diagnostics. Bioinformaticists would be called upon to answer a question about data; their role was to run an algorithm on a database that provided that answer. “But the subject has evolved from a service, like histology, to its own research arena…. Bioinformaticists are now the motor of the innovation,” he adds. They not only answer the data inquiries, but also, more importantly, determine what questions need to be asked in the first place.

As a result, “there are many opportunities for scientists to pursue a bioinformatics/big data career in the biotech/big pharma industry at the moment,” notes Jared Kaleck, senior director of computational chemistry/biology and formulation development at executive search firm Klein Hersh International.

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RNA测序可以检测人类和其他生物的基因表达情况。最近这一方法在生物科学和医学研究中非常流行，而且正在逐渐走向临床应用。与之前的方法相比，RNA测序的优势是便于研究选择性剪切形成的基因异构体或转录本。

那么RNA测序到底可不可靠呢？日前，由美国FDA牵头的测序质量控制(SEQC)项目对RNA测序的准确性、可重现性和信息含量进行了综合性评估，并将初步调查结果发表在近日的Nature Biotechnology杂志上。

研究团队使用RNA参照样本，在全球多个实验室的Illumina HiSeq、Life Technologies SOLiD、Roche 454平台上进行了检测。(深圳华大基因、复旦大学、华东师范大学等单位参与了这一项目。)研究人员主要是评估RNA测序在接头区域和差异性表达谱中的表现，并将其与芯片和定量PCR(qPCR)进行比较。

研究人员发现，所有测序深度都会出现未注释的外显子-外显子连接区域，其中80%以上都得到了qPCR的验证。用RNA测序检测相对表达可以得到准确且可重复的结果，但RNA测序和芯片都不能提供精确的绝对测量，而且研究用到的平台都存在基因特异性的偏好，包括qPCR。

数据分析的算法也会对RNA测序产生很大影响，不同算法生成的转录本数据差异很大。研究显示，赫尔辛基大学和曼彻斯特大学开发的BitSeq能生成最可靠的结果，这一方法以概率建模为基础。

这项研究获得的完整SEQC数据集拥有超过10Tb读取，为评估RNA测序分析提供了宝贵的资源。

目前，我遇到过两种JAVA block的情况.

一种是在建立http流之后，用conn.getInputStream().read()的时候block掉，这种情况通常是流再打开之后，网络出问题或者对方服务器问题等等。

通常写法是

while((is.read(buffer))!=-1){ do something }

网上通常的解决办法是用socket 来看是否超时，我的解决办法是 循环不要以is.read(buffer)作为判断语句。而是用is.available()做判断，如果availab总是返回0值，那么退出重连，这其实相当于自己判断是否block掉了。

另外一个就是在执行Runtime.getRuntime().exec(script)的时候，由于script报错太多，没有即使读取出来，导致java被block掉。

把网上的解决方案给大家。转自http://saluya.iteye.com/blog/1260347