BOL: Related items

Evolution and Cancer

Fri, 27 Sep 2013 11:28:49 -0500

Air date: Wednesday, January 04, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Category: Wednesday Afternoon Lectures Description: There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Dr. David Botstein, Princeton University Runtime: 00:59:58 Permanent link: http://videocast.nih.gov/launch.asp?17046

Troyanskaya Lab

Fri, 18 Oct 2013 10:57:40 -0500

In our research, we combine computational methods with an experimental component in a unified effort to develop comprehensive descriptions of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders, such as cancer, and others whose failure might produce developmental defects in model systems.

Research Interest
Genomic Data Integration

Microarray Analysis

Gene and Protein Function Prediction

Detection and Analysis of Chromosomal Abnormalities and Functional Evolution

Integration of Computation and Experiments

Identification of Biological Networks and Pathways

Evaluation and Validation of Computational Predictions

Scalable Visualization-Based Data Analysis

More @ http://reducio.princeton.edu/cm/
PI page @ http://reducio.princeton.edu/cm/ogt

Paper test for cancer !!!

Shruti Paniwala — Wed, 26 Feb 2014 00:20:30 -0600

The American Cancer Society projects the numbers of new cancer cases and deaths expected each year in order to estimate the contemporary cancer burden, because cancer incidence and mortality data lag three to four years behind the current year. In addition, the regularly updated Facts & Figures publications present the most current trends in cancer occurrence and survival, as well as information on symptoms, prevention, early detection, and treatment. Cancer rates in developing nations have climbed sharply in recent years, and now account for 70 percent of cancer mortality worldwide. Early detection has been proven to improve outcomes, but screening approaches such as mammograms and colonoscopy, used in the developed world, are too costly to be implemented in settings with little medical infrastructure.

The US born Sangeeta Bhatia at Massachusetts Institute of Technology (MIT) has developed a cheap, simple, paper test that can detect cancer. These diagnostic, which works much like a pregnancy test, could reveal within minutes, based on a urine sample, whether a person have cancer or not. The MIT media announce the major and amazing breakthrough in cancer diagonistics. These newly developed technology will allow non-communicable diseases to be detect at early stage, which will be cheap and easily accessible to the masses. For the developing world it would be exciting to adapt it instead to a paper test that could be performed on unprocessed samples in a rural setting, without the need for any specialized equipment. The simple readout could even be transmitted to a remote caregiver by a picture on a mobile phone.

The MIT professor and Howard Hughes Medical Institute investigator Sangeeta Bhatia, who is also the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, invented a new class of synthetic biomarker, which is highly specialized instrument to do these kind of analysis. These paper test essentially relies on nanoparticles that interact with tumor proteins called proteases, each of which can trigger release of hundreds of biomarkers that are then easily detectable in a patient's urine. The MIT nanoparticles are coated with peptides (short protein fragments) targeted by different MMPs. These particles congregate at tumor sites, where MMPs cleave hundreds of peptides, which accumulate in the kidneys and are excreted in the urine.

To create the test strips, the researchers first coated nitrocellulose paper with antibodies that can capture the peptides. Once the peptides are captured, they flow along the strip and are exposed to several invisible test lines made of other antibodies specific to different tags attached to the peptides. If one of these lines becomes visible, it means the target peptide is present in the sample. The technology can also easily be modified to detect multiple types of peptides released by different types or stages of disease.

In tests in mice, the researchers were able to accurately identify colon tumors, as well as blood clots. Bhatia says these tests represent the first step toward a diagnostic device that could someday be useful in human patients. "This is a new idea — to create an excreted biomarker instead of relying on what the body gives you," she says. "To prove this approach is really going to be a useful diagnostic, the next step is to test it in patient populations."

Reference:

Image: jasongrowclients

Homepage: http://lmrt.mit.edu/about.html

http://web.mit.edu/newsoffice/2014/a-paper-diagnostic-for-cancer-0224.html

http://timesofindia.indiatimes.com/home/science/PIO-develops-cheap-paper-test-to-detect-cancer/articleshow/30963615.cms

Scientist at Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra

Tue, 30 Aug 2016 04:16:15 -0500

Scientist
Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra
Scientist (One position)
Project: Bioinformatics centre DBT- Sub-DIC at ACTREC
Funding agency: DBT Grant No.232

Duration of the Project: Six Months from the date of appointment can be extended further for six months
Essential Qualification and Experience: 1st Class Masters Degree in Bioinformatics or Life Sciences equivalent degree from a recognized University with 4 years R&D experience in Bioinformatics or relevant subjects from recognized institutes.
OR
Ph.D. degree in Bioinformatics or Life Sciences from recognized University.
M.Sc. degree obtained after a one year course will not be considered.
Experience: Research/teaching experience in Bioinformatics or relevant subjects form recognized Institute(s).

More at http://www.actrec.gov.in/data%20files/Vacancies/2016/AV-scin-stud-trainee-6-Sept-16.docx

Computer scientist/bioinformatician at IEO in Milan, Italy

Thu, 31 Jan 2019 09:10:12 -0600

We are looking for a computer scientist or a bioinformatician with a strong computation background to join the bioinformatics unit of the IEO in Milan. Web development, scripting, experience with spring boot, hpc, docker are appreciated. The candidate will evolve in a research environment (next generation sequencing among others). The selected candidate will consolidate our team for the development and maintenance of the bioinformatics resources, and will have the opportunity to support the research groups in setting new tools and pipelines.

Place of employment and work

The candidate will be located at the Department of Experimental Oncology of the European Institute of Oncology in Milan (Italy), one of Europe’s leading research institutes in biomedical research, where he/she will also interact with one of the largest computational biology communities in Italy

Requirements:

The candidate should have a good knowledge of the UNIX system and good programming skills (bash, R, python, java). Background in bioinformatics would be appreciated but is not mandatory. Additional experience with containers (docker, singularity), grid computing, web frameworks, continuous integrations will be appreciated.

For further info or to arrange an informal interview, please write to arnaud.ceol@ieo.it

Gupta Lab

Sun, 15 Sep 2013 09:31:24 -0500

Gupta laboratory of Natural Information Processing at DA-IICT. Research in our lab currently focuses on two aspects of information processing viz. deciphering the information processing principles in life (systems biology) and making a computer out of bio-molecules. The key expertise of the lab is in error-correcting codes. We also work in classical and quantum information processing principles with expertise in coding theory and its wide variety of applications in Information and Communication Technology (ICT).

More @ http://www.guptalab.org/

Genomics and sequencing approach for identification of biomarkers to assess the efficacy of TGF-βRI inhibitors (of liver cancer) in vivo

Rahul Agarwal — Tue, 05 Aug 2014 13:55:32 -0500

Liver cancer is third leading cause of deaths and fourth most frequent occuring cancer worldwide. There are multiple signaling pathways responsible for causing cancer amongst which TGFb is most important cytokine whose signaling pathway promote cancer. However, main problem is to cure this cancer at late stage where we still have no treatment strategy to tackle this deadly cancer. Hence we need to find out new therapeutic target. One way is to look the relationships between mRNA, methylation and miRNA data of patients with different pathological conditions (cancer vs control either with inhibitor/not). MiRNA is small RNA molecules known to inhibit mRNA expression of particular gene by binding improperly to 3'UTR region of a gene and hence block binding of TF /translation of gene. CpG regions is known to located at promoter region of gene (5' UTR) and usually hypomethylated which allow to gene to transcribe and translate however sometime this region become hyper-methylated thats prevent expression of host gene. Thus , integration of these three data reveal new targets and pathways important for causing or preventing cancer and also reveal biomarker thats check the effects of inhibitor on signaling pathway underlying liver cancer.

Sidow Lab

Fri, 07 Dec 2018 09:06:30 -0600

We study mechanisms of cancer evolution by using state-of-the-art genomic approaches at the bench and in analysis. Accurate genome reconstruction is our other major area of interest. We also collaborate on important questions for which our expertise in genomics and computation is relevant. Arend's biosketch highlights some of our past contributions.

http://www.sidowlab.org/

Gamper Lab

Fri, 26 Mar 2021 07:45:02 -0500

Lab focuses on examining the mechanisms governing the signalling pathways from DNA damage sensing to the activation of stress-response genes. The long-term goal is to find proteins that are drug targets for cancer treatment (such as radiosensitizers for radiation therapy) or biomarkers that increase the predictive value of therapeutic outcome.

https://amgamper.weebly.com/

MIT Computational Biology Group

Thu, 18 Dec 2014 14:47:01 -0600

My research group consists primarily of computer science graduate students and postdocs with expertise in algorithms, statistical inferences and machine learning, and sharing a passion for understanding fundamental biological problems.

We work in a highly interdisciplinary environment at the interface of Computer Science and Biology. Since its inception, our lab has eagerly engaged in collaborative research partnerships with biological and experimental collaborators, facilitated by our affiliation with the Broad Institute and the Computational and Systems Biology initiative (CSBi) at MIT, our participation in the Epigenome Roadmap, ENCODE, and modENCODE consortia, and by several other ongoing collaborations at MIT, Harvard, and the Harvard Medical School affiliated hospitals.

http://compbio.mit.edu/