Big Data Analytics Issues and Challenges: A Survey

In the digital world data accumulation is increasing more and more. Billions of devices are connected worldwide already and expected to connect 50 billons of devices by the year 2020. All devices produce Peta bytes of information by transforming and sharing with light speed on optical and wireless networks. The fast growth of such large data facing numerous issues and challenges in big data analytics, as the rapid growth of variety of data, hardware platforms, software, speed and security. Utilizing the data in decision making is one of the big challenges. Scaling the platforms and frameworks are other important challenges. This paper surveys the characteristics of big data including its characteristics, issues and challenges, right choices of platforms and models depending on their computational requirements and challenges

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

Summary: The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase with important roles in many cellular processes as well as in cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. How these dimers relate to higher-order EGFR oligomers seen in cell membranes, however, remains unclear. Here, we used single-particle tracking (SPT) and Förster resonance energy transfer imaging to examine how each domain of EGFR contributes to receptor oligomerization and the rate of receptor diffusion in the cell membrane. Although the extracellular region of EGFR is sufficient to drive receptor dimerization, we find that the EGF-induced EGFR slowdown seen by SPT requires higher-order oligomerization—mediated in part by the intracellular tyrosine kinase domain when it adopts an active conformation. Our data thus provide important insight into the interactions required for higher-order EGFR assemblies involved in EGF signaling

\u3ci\u3eDrosophila\u3c/i\u3e Muller F Elements Maintain a Distinct Set of Genomic Properties Over 40 Million Years of Evolution

The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25–50%) than euchromatic reference regions (3–11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11–27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4–3.6 vs. 8.4–8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu