How Google Builds the Perfect Team

 

A large portion of our working lives is spent working in Teams. How we communicate with our team members is crucial to the success (or failure) of the team. In this week’s lesson, we looked at the Ego states (parent, adult, and child). We all know that effective teams operate in the Adult-Adult realm of conversation and feedback, however, sometimes a rift can occur and cause us to operate from a higher or lower level with each other. Then there are other ways to look at team dynamics.
In the video below Charles Duhigg discusses how Google builds the most effective teams.
How Google Builds the Perfect Team
Think back to some teams that you have been on that were especially dysfunctional or effective. Did they follow the team dynamics favored by Google or were they more directive in nature? What made them work (or not work)?
Q5
Part 1 draws on information from authors Narissa, Puntanunt-Carter and Thweatt, Interpersonal Communication: A Mindful Approach to Relationships.
Part I
Based on the reading this week in the lessons take a look at the following questions. Social media platforms provide individuals with increased opportunities to engage in online discussions.
How does social mediated communication benefit interpersonal communication?
How does it harm interpersonal communication?
How does your relationship with the person you are communicating with (or the lack of such a relationship) impact your social mediated communication style? How does the anonymity of social mediated communication impact communication styles?
How has social mediated communication impacted society as a whole? More specifically, how has social media impacted society?
How do past social mediated interactions influence your future decisions concerning mediated communication?
What factors do you consider when posting something on social media?
What aspects of netiquette do you practice the most when communicating online?
Q6

 

Sample Solution

There are more than 30 million single-nucleotide polymorphisms that are like a finger print of genetic code in human genome(37). International Haplotype Mapping Project characterizes these SNPs in variety of population for public usage(38). Researchers can use these databases to identify association between disease risk .disease studies and genome- wide association studies linked by commercially available microarrays (SNP chips)(39). When specific allele of a SNP is present , a fluorescent signal is produced by using allele specific oligonucleotide probes for SNP arrays and array have skill of analyzing up to 1 million SNPs in a single sample(40). Also allelic imbalance, copy number variation, or loss of heterozygosity of cancer genome can be screened by SNP array.

Microarray analysis

Expression levels of thousand gene in cancer is analyzed with single experiment of microarray. Microarrays that are chips have immobilized capture molecules serve as probes to bind fluorescently labeled targets prepared from the two samples for comparing (41). These capture molecules can be oligonucleotides or cDNA. MRNA, miRNA, DNA and protein microarrays are most popular analysis. Gene expression profiling has been used for catogarizing unique subtypes of cancer, identifying invasive and non invasive cancer type’s phenotype, forecasting prognosis and response to treatment and risk of recurrence(42). New miRNA microarray platform data’s can be used as a cancer biomarker. To classify patients prognostic groups and treatment subgroups, miRNA signatures is used. Also misroarray is used to determine epigectic alteration that is contributed to tumorigenesis and direct to manage patient(43).

Proteomics by mass spectrometry

Changing of protein profiles in cancer cell is important to determine new biomarker and might help to classify of tumors subtypes(44). Proteomic analysis have more advantage than measurement of mRNA. Because protein is the final effector molecule and their level can not overlap the level of mRNA due to the posttranscriptional modifications(45). In addition to that , protein-protein interactions contribute to cellular pathways and carcinogenesis. Proteins are quanrified in mass spectrometry according to their mass to

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