In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.

Q: In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al. (2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under more general settings where the first and third quartiles are also available for the trials. Through simulation studies, we demonstrate that the proposed methods greatly improve the existing methods and enrich the literature. We conclude our work with a summary table that serves as a comprehensive guidance for performing meta-analysis in different situations.

A: Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range
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Q: The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

A: Large-scale gene function analysis with the PANTHER classification system
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Q: Defined genetic models based on human pluripotent stem cells have opened new avenues for understanding disease mechanisms and drug screening. Many of these models assume cell-autonomous mechanisms of disease but it is possible that disease phenotypes or drug responses will only be evident if all cellular and extracellular components of a tissue are present and functionally mature. To derive optimal benefit from such models, complex multicellular structures with vascular components that mimic tissue niches will thus likely be necessary. Here we consider emerging research creating human tissue mimics and provide some recommendations for moving the field forward.

A:
Complex Tissue and Disease Modeling using hiPSCs.
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