Showing posts with label Lecture and Tutorials. Show all posts
Showing posts with label Lecture and Tutorials. Show all posts

Escape analysis and lock coarsening in JAVA 6.0


The popularity of the Java programming language has made escape analysis a target of interest. Java's combination of heap-only object allocation, built-in threading, and the Sun HotSpot dynamic compiler creates a candidate platform for escape analysis related optimizations. Escape analysis is implemented in Java Standard Edition 6.


Example (Java)

class A {
  final int finalValue;
 
  public A( B b ) {
    super();
    b.doSomething( this ); // this escapes!
    finalValue = 23;
  }
 
  int getTheValue() {
    return finalValue;
  }
}
 
class B {
  void doSomething( A a ) {
    System.out.println( a.getTheValue() );
  }
}
In this example, the constructor for class A passes the new instance of A to B.doSomething. As a result, the instance of A—and all of its fields—escapes the scope of the constructor.

Java is able to manage multithreading at the language level. Multithreading is a technique that allows programs to operate faster on computer system that have multiple CPUs. Also, a multithreaded application has the ability to remain responsive to input, even when it is performing long running tasks.
However, programs that use multithreading need to take extra care of objects shared between threads, locking access to shared methods or blocks when they are used by one of the threads. Locking a block or an object is a time-consuming operation due to the nature of the underlying operating system-level operation involved .
As the Java library does not know which methods will be used by more than one thread, the standard library always locks blocks when necessary in a multithreaded environment.
Prior to Java 6, the virtual machine always locked objects and blocks when asked to by the program even if there was no risk of an object being modified by two different threads at the same time. For example, in this case, a local Vector was locked before each of the add operations to ensure that it would not be modified by other threads (Vector is synchronized), but because it is strictly local to the method this is not necessary:
public String getNames() {
     Vector v = new Vector();
     v.add("Me");
     v.add("You");
     v.add("Her");
     return v.toString();
}
Starting with Java 6, code blocks and objects are locked only when necessary , so in the above case, the virtual machine would not lock the Vector object at all

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Andrew Dalke's Slides for Introduction to Python


I came across a nice set of slides from a course that Andrew Dalke taught a few years ago. They give a great introduction to Python for people interested in Bioinformatics. Here is a link (scroll to the very bottom of the page).

Andrew has a
blog, and a company with a presence on the web (where the slides are hosted), and he's on Stack Overflow as dalke.

Thanks, Andrew.



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Downloads section



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The Human Genome Project



About the Lecture

Dr. Lander is a geneticist, molecular biologist and a mathematician, with research interests in human genetics, mouse genetics, population genetics and computational and mathematical methods in biology.

He and his research group have developed many of the tools of modern genome research including genomic maps of the human, mouse and rat genomes in connection with the Human Genome Project and techniques for genetic analyses of complex, multigenic traits. He has applied these techniques to the understanding of cancer, diabetes, hypertension, renal failure and dwarfism.

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Recombinant DNA Lecture by Eric S.Lander

Eric Lander was a world leader of the international Human Genome Project, the effort to map the blueprint for a human being. Today, Lander is using the knowledge of the human genome to tackle the fundamental issue of medicine: to find the causes of disease.

Lander received his Ph.D. in mathematics from Oxford in 1981, as a Rhodes Scholar. He joined Whitehead Institute in 1986 and founded the Whitehead Institute/MIT Center for Genome Research in 1990. Lander became the founding director of the newly created Broad Institute in 2003.
Lander is a member of the U.S. National Academy of Sciences, and U.S. Institute of Medicine. He was a MacArthur Fellow (1987-1992), and earned the Woodrow Wilson Prize from Princeton University(1998); the Baker Memorial Award for Undergraduate Teaching at MIT (1992); the City of Medicine Prize (2001); and the Gairdner International Prize (2002).

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Using Dendritic Cells to Create Cancer Vaccines

Edgar Engleman, MD, medical director of the Stanford Blood Center, discusses his research involving the use of a special type of white blood cell as a treatment for cancer. Engleman, who is also a professor of pathology at the Stanford School of Medicine, and his team of researchers have been interested in dendritic cells, or DCs, which can provoke an immune response in the body.
The goal of this laboratory is to better understand dendritic cell biology with the objective of using this information to discover and develop more effective immunotherapeutic approaches to disease. We pursue this goal by performing experiments in both mice and humans. In our initial clinical studies antigen pulsed dendritic cells were administered to patients with cancer or life-threatening viral infections in order to induce specific immunity. The results of these trials have been extremely encouraging. More recently we have focused our studies on the development and life cycle of dendritic cells, including Langerhans cells, and the results have not only shed new light on dendritic cell biology but also have led to our ability to target dendritic cells in vivo without having to manipulate these cells in vitro. We believe that this new approach will eventually make it possible to downregulate as well as upregulate the immune system in an antigen specific manner.

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Biotechnology - Will It Create a New Industry?

Henri Termeer discusses growth of the 25-year-old biotech industry, including international mergers, R&D challenges and "product based" companies verses "platform based" companies
About the Speaker
Henri A. Termeer,President and CEO, Genzyme Corporation

Henri A. Termeer was appointed president of the Genzyme Corporation in 1983 and became the chief executive officer in 1985 and chairman in 1988. Under his leadership, Genzyme has grown from a modest entrepreneurial venture into one of the world's top five biotechnology companies. Mr. Termeer is known worldwide for his contributions to the biotechnology industry and particularly noted for his expertise in financing new initiatives. His innovative approaches have earned Genzyme the Laguna Niguel Best of Biotech Award in 1991 and 1994, as well as the Laguna Niguel Hall of Fame Award in 1997.

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An overivew of the KEGG bioinformatics website-Video Tutorial

An overivew of the KEGG bioinformatics website






An overivew of the KEGG bioinformatics website. As an example, protein and gene information is examined for the antibiotic resistance enzyme secreted by the bacterium Eschericia coli. 1280×720.


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How to do NCBI BLAST Analysis? - Free Video tutorial

How to do NCBI BLAST Analysis ?












BLAST Analysis of Woolly Mammoth DNA using the NCBI Blastn tool. 940×716 resolution.

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Overview of the UniProt Bioinformatics Website-Free Video Tutorial

UniProt is the universal protein resource, a central repository of protein data created by combining Swiss-Prot, TrEMBL and PIR. This makes it the world’s most comprehensive resource on protein information.

UniProt provides four core database:

* The UniProt Knowledgebase (UniProtKB) is the central database of protein sequences with accurate, consistent, and rich sequence and functional annotation.

* The UniProt Reference Clusters (UniRef) databases provide non-redundant reference data collections based on the UniProt knowledgebase in order to obtain complete coverage of sequence space at several resolutions.

* The UniProt Metagenomics and Environmental Sequences database (UniMES) is a repository specifically developed for metagenomic and environmental sequence data.

* The UniProt Archive (UniParc) provides a stable, comprehensive sequence collection without redundant sequences by storing the complete body of publicly available protein sequence data.

This video tutorial gives an overview of the UniProt bioinformatics website. To show its practical application, the human protein college is researched, its amino acid sequence is discovered, and the blastp tool is used to BLAST the protein to find organisms having collagen with similarity.


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Evolution of the protein kinase family

Evolution of the protein kinase family - Video Lecture A protein kinase is a kinase enzyme that modifies other proteins by chemically adding phosphate groups to them (phosphorylation). Phosphorylation usually results in a functional change of the target protein (substrate) by changing enzyme activity, cellular location, or association with other proteins.












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Python Programming-Video Tutorials

Python is a general-purpose high-level programming language. Its design philosophy emphasizes code readability.Python’s core syntax and semantics are minimalistic, while the standard library is large and comprehensive. Its use of indentation as block delimiters is unusual among popular programming languages.








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How to make Phylogram-Video TutorialHow to make Phylogram-Video Tutorial

A Phylogenetic tree or Phylogram, sometimes called the ‘Tree of Life’, shows the evolutionary relationships among various biological species or other entities that are believed to have a common ancestor. Each node with descendants represents the most recent common ancestor of the descendants, with edge lengths in our tree, corresponding to time estimates. Each node in a phylogenetic tree is called a taxonomic unit.

This video tutorial explains how to make your own phylogram. Steps include getting Homologene from NCBI website, using EBI clustalW for creating phylogram.




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Statistical Aspects of Datamining-Video Course

Data Mining is used to discover patterns and relation-ships in data, with an emphasis on large observational data bases. Despite the obvious connections between data mining and statistical data analysis, most of the methodologies used in Data Mining have so far originated in elds other than Statistics. This course video tutorial gives introduction to datamining, statistical aspects of datamining, with training on R statistics software.

Course:Statistical Aspects of Data Mining
Course teacher:Professor David Mease
Courtsey:Standford University,Google tech talks





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Computer Aided Drug Designing


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Proteomics


LectureSpeakerDownload
1.0 Introduction to ProteomicsDavid WishartDownload PPT Download PDF
1.1 High Throughput Methods in ProteomicsDavid WishartDownload PPT Download PDF
1.2 Keynote LectureMichel DumontierDownload PPT Download PDF
1.3 Lecture: Analysis of 2D GelsDavid WishartDownload PPT Download PDF
1.4 Lab: GelScape and GelBankDavid WishartDownload PPT Download PDF
2.1 Lecture: Mass Spectrometry Methods and TheoryDavid WishartDownload PPT Download PDF
2.2 Lecture: Mass Spectrometry Applications to ProteomicsDavid WishartDownload PPT Download PDF
2.3 Lecture: MSMSDavid WishartDownload PPT Download PDF
2.4 Lab: Mascot and more MSMSDavid WishartDownload PPT Download PDF
2.5 Lecture: MSMSDavid WishartDownload PPT Download PDF
3.0 Lecture: Protein Expression and Structural ProteomicsDavid WishartDownload PPT Download PDF
3.1 Lecture: Methods in 3D Structure DeterminationDavid WishartDownload PPT Download PDF
3.2 Lecture: Predicting and Classifying Protein Structures and SuperpositionMichel DumontierDownload PPT Download PDF
3.3a Lecture: Homology ModelingBoris SteipeDownload PPT Download PDF
3.3b Lecture: ThreadingBoris SteipeDownload PPT Download PDF
3.4 Lecture: Visualization ToolsBoris SteipeDownload PPT Download PDF
3.5 Lab: Modeling and ThreadingBoris Steipeno slides
4.0 Lecture: Subcellular LocalizationShan SundararajDownload PPT Download PDF
4.1 Lecture: Protein InteractionsMichel DumontierDownload PPT Download PDF
4.2 Lab slides: Protein InteractionsMichel DumontierDownload PPT Download PDF
4.3 Lecture: Small Molecule-Protein InteractionsHoward FeldmanDownload PPT Download PPT
4.4 Lecture: Protein pathway databasesShan SundararajDownload PPT Download PDF
5.0 Lecture: Organellar Proteomics and BioinformaticsJohn BergeronDownload PPT Download PDF
5.1 Lecture: So... What Comes After Bioinformatics?Mike EllisonDownload PPT Download PDF
5.2 Lecture: Ab Initio Structure PredictionHoward FeldmanDownload PPT Download PDF
5.3 Lecture: Systems BiologyBoris SteipeDownload PDF


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