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@PHDTHESIS{Asp2018-rr,
title = "Spatially Resolved Gene Expression Analysis",
author = "Asp, Michaela",
year = 2018,
school = "KTH Royal Institute of Technology",
keywords = "Mendeley Import (Feb 23)"
}
@MISC{Somers2018-pu,
title = "The friendship that made Google huge",
booktitle = "The New Yorker",
author = "Somers, J",
year = 2018,
howpublished = "\url{https://www.newyorker.com/magazine/2018/12/10/the-friendship-that-made-google-huge}",
keywords = "Mendeley Import (Feb 23)"
}
@MISC{Birgitta2020-kb,
title = "On Pair Progamming",
author = "Birgitta, Bockeler and Siessegger, Nina",
year = 2020,
howpublished = "\url{https://martinfowler.com/articles/on-pair-programming.html}",
keywords = "Mendeley Import (Feb 23)"
}
@INPROCEEDINGS{Bjorklund2020-hk,
title = "Exploring the Impact of Mob Programming on the {Well-Being} of
Developers: Insights from a Software Company",
author = "Bj{\"o}rklund, Philip and Fridebo, Jacob and Dalipi, Fisnik",
year = 2020,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Hui2011-oh,
title = "Pair Programming and {LSs} in Computing Education: Its Impact on
Students' Performances",
author = "Hui, Tie Hui and Umar, Irfan Naufal",
abstract = "Learning to programme requires complex cognitive skills that
computing students find it arduous in comprehension. PP (pair
programming) is an intensive style of programme cooperation where
two people working together in resolving programming scenarios.
It begins to draw the interests of educators as a teaching
approach to facilitate learning and improve programming
performance. The approach of PP, its model, benefits and
limitations as well as the LS (learning style) preference are
presented in the first part of this paper. The research findings
and discussion on the application of PP involving 96 first year
computing students are incorporated in the second part of this
paper. The participants in these two intact classes were randomly
assigned either to the experimental group that received PP or to
the control group that received DI (direct instruction) method
only. In PP group, students worked in pairs based on the
visual-verbal LS dimension and those of DI group work
individually. During a seven-week treatment, both groups applied
program flowcharts and pseudocode in solving programming tasks.
This study used two assessment methods--the formative and
summative to examine the students' programming achievements. Two
programming assignments were used as a formative assessment tool,
also the CPPT (computer programming performance test) as the
second tool which comprises of a pre-test, an immediate post-test
and a delayed post-test, was administrated to assess the
students' programming recall and retention. The result findings
indicated that students in PP group significantly outperformed
those in DI group for both the formative and summative
assessments. However, only the visual and verbal students
performed significantly better in recall than the retention. The
analysis on the interaction effects revealed that learning is
within inner self with regard to the instructional strategies
applied and LS preference in classroom environment. In this case,
the effectiveness of instructional strategies adopted to foster
learning somehow depends on the type of learners. Therefore,
educators should reflect on individual learning abilities while
applying PP to stimulate students' engagement and critical
thinking skills that subsequently will have positive influence on
academic performance. (Contains 4 figures and 3 tables.)",
journal = "Online Submission",
year = 2011,
keywords = "Cognitive Style; College Students; Comparative Analysis; Computer
Science Education; Control Groups; Cooperative Learning; Direct
Instruction; Educational Strategies; Experimental Groups;
Formative Evaluation; Instructional Effectiveness; Interaction;
Learning Modalities; Learning Processes; Preferences; Pretests
Posttests; Programming; Quasiexperimental Design; Recall
(Psychology); Retention (Psychology); Summative
Evaluation;Mendeley Import (Feb 23)"
}
@INPROCEEDINGS{Srikanth2004-ql,
title = "On pair rotation in the computer science course",
booktitle = "Software Engineering Education Conference, Proceedings",
author = "Srikanth, Hema and Williams, Laune and Wiebe, Eric and Miller,
Carol and Balik, Suzanne",
abstract = "In a course environment, pairing a student with one partner for
the entire semester is beneficial, but may not be optimal. The
authors conducted a study in two undergraduate level courses to
observe the advantages and disadvantages of pair rotation
whereby a student pairs with several different students
throughout the semester. This paper summarizes teaching staff
and student perceptions on the viability of pair rotation.
Teachers find pair rotation valuable because the teaching staff
can obtain multiple peer evaluations on each student and because
dysfunctional pairs are regularly disbanded. However, pair
rotation adds to the burden of assigning pairs multiple times
per semester. The majority of students in the study perceived
pair rotation to be a desirable approach. Additionally, most
students considered peer evaluation to be an effective means of
providing feedback to teaching staff. However, they did not
significantly believe that peer evaluation was an effective
means for motivating students.",
year = 2004,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Nosek1998-hy,
title = "The Case for Collaborative Programming",
author = "Nosek, John T",
journal = "Commun. ACM",
year = 1998,
keywords = "Mendeley Import (Feb 23)"
}
@INPROCEEDINGS{Bird2013-je,
title = "Expectations, Outcomes, and Challenges of Modern Code Review",
booktitle = "Proceedings of the International Conference on Software
Engineering",
author = "Bird, Christian and Bacchelli, Alberto",
abstract = "Code review is a common software engineering practice employed
both in open source and industrial contexts. Review today is
less formal and more ``lightweight'' than the code inspections
performed and studied in the 70s and 80s. We empirically explore
the motivations, challenges, and outcomes of tool-based code
reviews. We observed, interviewed, and surveyed developers and
managers and manually classified hundreds of review comments
across diverse teams at Microsoft. Our study reveals that while
finding defects remains the main motivation for review, reviews
are less about defects than expected and instead provide
additional benefits such as knowledge transfer, increased team
awareness, and creation of alternative solutions to problems.
Moreover, we find that code and change understanding is the key
aspect of code reviewing and that developers employ a wide range
of mechanisms to meet their understanding needs, most of which
are not met by current tools. We provide recommendations for
practitioners and researchers.",
publisher = "IEEE",
month = may,
year = 2013,
keywords = "Mendeley Import (Feb 23)"
}
@INPROCEEDINGS{Doutreligne2014-ly,
title = "{UnityMol}: Interactive scientific visualization for integrative
biology",
booktitle = "{IEEE} Symposium on Large Data Analysis and Visualization 2014,
{LDAV} 2014 - Proceedings",
author = "Doutreligne, S{\'e}bastien and Cragnolini, Tristan and Pasquali,
Samuela and Derreumaux, Philippe and Baaden, Marc",
abstract = "A broad challenge facing scientists today is the availability of
huge amounts of data from various sources. Computers are
required to store, analyze, explore and represent these data in
order to extract useful information. With UnityMol, we pursue
the ambitious goal to create an interactive virtual laboratory
enabling researchers in biology to visualize biomolecular
systems, run simulations and interact with physical models and
data. Visual effects can enrich the dynamic and immersive
aspects. Ultimately, we want to combine an appealing visual
feedback already in place with a set of analysis features to
extract information about properties of the fascinating
biomolecular systems under study.",
year = 2014,
keywords = "Biology and Genetics; I.6.6 [Simulation and Modeling];
Simulation Output Analysis; J.3 [Computer Applicat;Mendeley
Import (Feb 23)"
}
@ARTICLE{Xu2020-xz,
title = "{VRmol}: an Integrative {Web-Based} Virtual Reality System to
Explore Macromolecular Structure",
author = "Xu, Kui and Liu, Nan and Xu, Jingle and Guo, Chunlong and Zhao,
Lingyun and Wang, Hong-Wei and Zhang, Qiangfeng Cliff",
abstract = "Structural visualization and analysis are fundamental to explore
macromolecular functions. Here we present a novel integrative
web-based virtual reality (VR) system - VRmol, to visualize and
study molecular structures in an immersive virtual environment.
Importantly, it is integrated with multiple online databases and
able to couple structure studies with associated genomic
variations and drug information in a visual interface by
cloud-based drug docking. VRmol thus can serve as an integrative
platform to aid structure-based translational research and drug
design. VRmol is freely available (https://VRmol.net), with
detailed manual and tutorial (https://VRmol.net/docs). The code
of VRmol is available as open source under the MIT license at
http://github.com/kuixu/VRmol. Supplementary data are available
at Bioinformatics online.",
journal = "Bioinformatics",
year = 2020,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Stefani2018-om,
title = "{ConfocalVR}: Immersive Visualization for Confocal Microscopy",
author = "Stefani, Caroline and Lacy-Hulbert, Adam and Skillman, Thomas",
abstract = "ConfocalVR is a virtual reality (VR) application created to
improve the ability of researchers to study the complexity of
cell architecture. Confocal microscopes take pictures of
fluorescently labeled proteins or molecules at different focal
planes to create a stack of two-dimensional images throughout the
specimen. Current software applications reconstruct the
three-dimensional (3D) image and render it as a two-dimensional
projection onto a computer screen where users need to rotate the
image to expose the full 3D structure. This process is mentally
taxing, breaks down if you stop the rotation, and does not take
advantage of the eye's full field of view. ConfocalVR exploits
consumer-grade VR systems to fully immerse the user in the 3D
cellular image. In this virtual environment, the user can (1)
adjust image viewing parameters without leaving the virtual
space, (2) reach out and grab the image to quickly rotate and
scale the image to focus on key features, and (3) interact with
other users in a shared virtual space enabling real-time
collaborative exploration and discussion. We found that immersive
VR technology allows the user to rapidly understand cellular
architecture and protein or molecule distribution. We note that
it is impossible to understand the value of immersive
visualization without experiencing it first hand, so we encourage
readers to get access to a VR system, download this software, and
evaluate it for yourself. The ConfocalVR software is available
for download at http://www.confocalvr.com, and is free for
nonprofits.",
journal = "J. Mol. Biol.",
year = 2018,
keywords = "ImageJ; cellular visualization; confocal microscopy; virtual
collaboration; virtual reality;Mendeley Import (Feb 23)"
}
@ARTICLE{Theart2017-dk,
title = "Virtual reality assisted microscopy data visualization and
colocalization analysis",
author = "Theart, Rensu P and Loos, Ben and Niesler, Thomas R",
abstract = "Background: Confocal microscopes deliver detailed
three-dimensional data and are instrumental in biological
analysis and research. Usually, this three-dimensional data is
rendered as a projection onto a two-dimensional display. We
describe a system for rendering such data using a modern virtual
reality (VR) headset. Sample manipulation is possible by
fully-immersive hand-tracking and also by means of a conventional
gamepad. We apply this system to the specific task of
colocalization analysis, an important analysis tool in biological
microscopy. We evaluate our system by means of a set of user
trials. Results: The user trials show that, despite inaccuracies
which still plague the hand tracking, this is the most productive
and intuitive interface. The inaccuracies nevertheless lead to a
perception among users that productivity is low, resulting in a
subjective preference for the gamepad. Fully-immersive
manipulation was shown to be particularly effective when defining
a region of interest (ROI) for colocalization analysis.
Conclusions: Virtual reality offers an attractive and powerful
means of visualization for microscopy data. Fully immersive
interfaces using hand tracking show the highest levels of
intuitiveness and consequent productivity. However, current
inaccuracies in hand tracking performance still lead to a
disproportionately critical user perception.",
journal = "BMC Bioinformatics",
year = 2017,
keywords = "3D Microscopic reconstruction; Colocalization analysis; Confocal
microscopy visualization; Hand tracking; Region of interest
selection; Virtual reality; Volume rendering;Mendeley Import (Feb
23)"
}
@ARTICLE{Blanc2020-hs,
title = "Genuage: visualize and analyze multidimensional single-molecule
point cloud data in virtual reality",
author = "Blanc, Thomas and El Beheiry, Mohamed and Caporal, Cl{\'e}ment
and Masson, Jean Baptiste and Hajj, Bassam",
abstract = "Experimentally recorded point cloud data, such as those generated
by single-molecule localization microscopy, are continuously
increasing in size and dimension. Gaining an intuitive
understanding and facilitating the analysis of such
multidimensional data remains challenging. Here we report a new
open-source software platform, Genuage, that enables the easy
perception of, interaction with and analysis of multidimensional
point clouds in virtual reality. Genuage is compatible with
arbitrary multidimensional data extending beyond single-molecule
localization microscopy.",
journal = "Nat. Methods",
year = 2020,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Yang2018-cv,
title = "starmap: Immersive visualisation of single cell data using
smartphone-enabled virtual reality",
author = "Yang, Andrian and Yao, Yu and Li, Jianfu and Ho, Joshua",
abstract = "We report a new smartphone-enabled virtual reality (VR) program,
starmap (https://vccri.github.io/starmap/), that enables
immersive visualisation of single-cell data for hundreds of
thousands of cells using a mobile-enabled web browser and
low-cost VR head mount device.",
journal = "bioRxiv",
year = 2018,
keywords = "Bioinformatics; Biology; Computer graphics (images); Immersion
(virtual reality); Mount; Virtual reality; Visualization;Mendeley
Import (Feb 23)"
}
@ARTICLE{Stein2020-np,
title = "{singlecellVR}: interactive visualization of single-cell data in
virtual reality",
author = "Stein, David F and Chen, Huidong and Vinyard, Michael E and
Pinello, Luca",
abstract = "Single-cell assays have transformed our ability to model
heterogeneity within cell populations and tissues. Virtual
reality has recently emerged as a powerful technology to
dynamically explore complex data. However, expensive hardware or
advanced data preprocessing skills are required to adapt such
technology to single-cell data. To address current shortcomings,
we built singlecellVR, a user-friendly website for visualizing
single-cell data, designed for cheap and easily available virtual
reality hardware (e.g., Google Cardboard, ~\$8). We provide a
companion package, scvr to streamline data conversion from the
most widely-adopted single-cell analysis tools and a database of
pre-analyzed datasets to which users can contribute.Competing
Interest StatementThe authors have declared no competing
interest.",
journal = "bioRxiv",
pages = "2020.07.30.229534",
month = jan,
year = 2020,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Poco2011-bx,
title = "A framework for exploring multidimensional data with {3D}
projections",
author = "Poco, J and Etemadpour, R and Paulovich, F V and Long, T V and
Rosenthal, P and Oliveira, M C F and Linsen, L and Minghim, R",
abstract = "Visualization of high-dimensional data requires a mapping to a
visual space. Whenever the goal is to preserve similarity
relations a frequent strategy is to use 2D projections, which
afford intuitive interactive exploration, e.g., by users locating
and selecting groups and gradually drilling down to individual
objects. In this paper, we propose a framework for projecting
high-dimensional data to 3D visual spaces, based on a
generalization of the Least- Square Projection (LSP). We compare
projections to 2D and 3D visual spaces both quantitatively and
through a user study considering certain exploration tasks. The
quantitative analysis confirms that 3D projections outperform 2D
projections in terms of precision. The user study indicates that
certain tasks can be more reliably and confidently answered with
3D projections. Nonetheless, as 3D projections are displayed on
2D screens, interaction is more difficult. Therefore, we
incorporate suitable interaction functionalities into a framework
that supports 3D transformations, predefined optimal 2D views,
coordinated 2D and 3D views, and hierarchical 3D cluster
definition and exploration. For visually encoding data clusters
in a 3D setup, we employ color coding of projected data points as
well as four types of surface renderings. A second user study
evaluates the suitability of these visual encodings. Several
examples illustrate the framework's applicability for both visual
exploration of multidimensional abstract (non-spatial) data as
well as the feature space of multi-variate spatial data.
\copyright{} 2011 The Author(s).",
journal = "Comput. Graph. Forum",
year = 2011,
keywords = "Mendeley Import (Feb 23)"
}
@INPROCEEDINGS{Colange2019-sl,
title = "Interpreting Distortions in Dimensionality Reduction by
Superimposing Neighbourhood Graphs",
booktitle = "2019 {IEEE} Visualization Conference, {VIS} 2019",
author = "Colange, Benoit and Vuillon, Laurent and Lespinats, Sylvain and
Dutykh, Denys",
abstract = "To perform visual data exploration, many dimensionality
reduction methods have been developed. These tools allow data
analysts to represent multidimensional data in a 2D or 3D space,
while preserving as much relevant information as possible. Yet,
they cannot preserve all structures simultaneously and they
induce some unavoidable distortions. Hence, many criteria have
been introduced to evaluate a map's overall quality, mostly
based on the preservation of neighbourhoods. Such global
indicators are currently used to compare several maps, which
helps to choose the most appropriate mapping method and its
hyperparameters. However, those aggregated indicators tend to
hide the local repartition of distortions. Thereby, they need to
be supplemented by local evaluation to ensure correct
interpretation of maps.In this paper, we describe a new method,
called MING, for ``Map Interpretation using Neighbourhood
Graphs''. It offers a graphical interpretation of pairs of map
quality indicators, as well as local evaluation of the
distortions. This is done by displaying on the map the nearest
neighbours graphs computed in the data space and in the
embedding. Shared and unshared edges exhibit reliable and
unreliable neighbourhood information conveyed by the mapping. By
this mean, analysts may determine whether proximity (or
remoteness) of points on the map faithfully represents
similarity (or dissimilarity) of original data, within the
meaning of a chosen map quality criteria. We apply this approach
to two pairs of widespread indicators: precision/recall and
trustworthiness/continuity, chosen for their wide use in the
community, which will allow an easy handling by users.",
year = 2019,
keywords = "Evaluation - Qualitative Evaluation; Non-Spatial Data and
Techniques - Dimensionality R; Visual Analysis and Knowledge
Discovery - Visual K;Mendeley Import (Feb 23)"
}
@ARTICLE{Sanftmann2012-zp,
title = "{3D} scatterplot navigation",
author = "Sanftmann, Harald and Weiskopf, Daniel",
abstract = "For 3D scatterplots, we present an interpolation and projection
technique that supports the smooth exchange of one or two data
dimensions at a time. Even though this exchange can be considered
as a rotation in 4D or 5D data domains, we guarantee that the
projection to image space is perceived as a 3D rigid body
rotation---with a consistent motion of the data points. We
conducted a controlled user study showing that 3D rigid body
rotations outperform direct transition between scatterplots. We
further extend our technique to support navigation between 3D
scatterplots by introducing 3D scatterplot matrices. The
usefulness of our approach is demonstrated by application
examples, including a case study with a natural language
processing expert. \copyright{} 1995-2012 IEEE.",
journal = "IEEE Trans. Vis. Comput. Graph.",
year = 2012,
keywords = "Visualization; coordinated and multiple views; multidimensional
data; scatterplot;Mendeley Import (Feb 23)"
}
@ARTICLE{Coimbra2016-ba,
title = "Explaining three-dimensional dimensionality reduction plots",
author = "Coimbra, Danilo B and Martins, Rafael M and Neves, T{\'a}cito T A
T and Telea, Alexandru C and Paulovich, Fernando V",
abstract = "Understanding three-dimensional projections created by
dimensionality reduction from high-variate datasets is very
challenging. In particular, classical three-dimensional
scatterplots used to display such projections do not explicitly
show the relations between the projected points, the viewpoint
used to visualize the projection, and the original data
variables. To explore and explain such relations, we propose a
set of interactive visualization techniques. First, we adapt and
enhance biplots to show the data variables in the projected
threedimensional space. Next, we use a set of interactive bar
chart legends to show variables that are visible from a given
viewpoint and also assist users to select an optimal viewpoint to
examine a desired set of variables. Finally, we propose an
interactive viewpoint legend that provides an overview of the
information visible in a given three-dimensional projection from
all possible viewpoints. Our techniques are simple to implement
and can be applied to any dimensionality reduction technique. We
demonstrate our techniques on the exploration of several
real-world high-dimensional datasets.",
journal = "Inf. Vis.",
year = 2016,
keywords = "Dimensionality reduction; Explanatory visualization; Multivariate
visualization; Scatterplots;Mendeley Import (Feb 23)"
}
@ARTICLE{Packer2019-we,
title = "A lineage-resolved molecular atlas of C. Elegans embryogenesis at
single-cell resolution",
author = "Packer, Jonathan S and Zhu, Qin and Huynh, Chau and
Sivaramakrishnan, Priya and Preston, Elicia and Dueck, Hannah and
Stefanik, Derek and Tan, Kai and Trapnell, Cole and Kim, Junhyong
and Waterston, Robert H and Murray, John I",
abstract = "Caenorhabditis elegans is an animal with few cells but a wide
diversity of cell types. In this study, we characterize the
molecular basis for their specification by profiling the
transcriptomes of 86,024 single embryonic cells. We identify 502
terminal and preterminal cell types, mapping most single-cell
transcriptomes to their exact position in C. elegans' invariant
lineage. Using these annotations, we find that (i) the
correlation between a cell's lineage and its transcriptome
increases from middle to late gastrulation, then falls
substantially as cells in the nervous system and pharynx adopt
their terminal fates; (ii) multilineage priming contributes to
the differentiation of sister cells at dozens of lineage
branches; and (iii) most distinct lineages that produce the same
anatomical cell type converge to a homogenous transcriptomic
state.",
journal = "Science",
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Qadir2020-ds,
title = "Single-cell resolution analysis of the human pancreatic ductal
progenitor cell niche",
author = "Qadir, Mirza Muhammad Fahd and {\'A}lvarez-Cubela, Silvia and
Klein, Dagmar and van Dijk, Jasmijn and Mu{\~n}iz-Anquela,
Roc{\'\i}o and Moreno-Hern{\'a}ndez, Yaisa B and Lanzoni, Giacomo
and Sadiq, Saad and Navarro-Rubio, Bel{\'e}n and Garc{\'\i}a,
Michael T and D{\'\i}az, {\'A}ngela and Johnson, Kevin and Sant,
David and Ricordi, Camillo and Griswold, Anthony and Pastori,
Ricardo Luis and Dom{\'\i}nguez-Bendala, Juan",
abstract = "We have described multipotent progenitor-like cells within the
major pancreatic ducts (MPDs) of the human pancreas. They express
PDX1, its surrogate surface marker P2RY1, and the bone
morphogenetic protein (BMP) receptor 1A (BMPR1A)/activin-like
kinase 3 (ALK3), but not carbonic anhydrase II (CAII). Here we
report the single-cell RNA sequencing (scRNA-seq) of
ALK3bright+-sorted ductal cells, a fraction that harbors
BMP-responsive progenitor-like cells. Our analysis unveiled the
existence of multiple subpopulations along two major axes, one
that encompasses a gradient of ductal cell differentiation
stages, and another featuring cells with transitional phenotypes
toward acinar tissue. A third potential ducto-endocrine axis is
revealed upon integration of the ALK3bright+ dataset with a
single-cell whole-pancreas transcriptome. When transplanted into
immunodeficient mice, P2RY1+/ALK3bright+ populations (enriched in
PDX1+/ALK3+/CAII− cells) differentiate into all pancreatic
lineages, including functional $\beta$-cells. This process is
accelerated when hosts are treated systemically with an ALK3
agonist. We found PDX1+/ALK3+/ CAII− progenitor-like cells in the
MPDs of types 1 and 2 diabetes donors, regardless of the duration
of the disease. Our findings open the door to the pharmacological
activation of progenitor cells in situ.",
journal = "Proc. Natl. Acad. Sci. U. S. A.",
year = 2020,
keywords = "Human pancreatic progenitors; Islet regeneration; Single-cell RNA
sequencing; Transplantation; Type 1 diabetes;Mendeley Import (Feb
23)"
}
@ARTICLE{Cakir2020-no,
title = "Comparison of visualisation tools for single-cell {RNAseq} data",
author = "Cakir, Batuhan and Prete, Martin and Huang, Ni and van Dongen,
Stijn and Pir, Pnar and Kiselev, Vladimir Yu",
abstract = "In the last decade, single cell RNAseq (scRNAseq) datasets have
grown from a single cell to millions of cells. Due to its high
dimensionality, the scRNAseq data contains a lot of valuable
information, however, it is not always feasible to visualise and
share it in a scientific report or an article publication format.
Recently, a lot of interactive analysis and visualisation tools
have been developed to address this issue and facilitate
knowledge transfer in the scientific community. In this study, we
review and compare several of the currently available analysis
and visualisation tools and benchmark those that allow to
visualize the scRNAseq data on the web and share it with others.
To address the problem of format compatibility for most
visualisation tools, we have also developed a user-friendly R
package, sceasy, which allows users to convert their own scRNAseq
datasets into a specific data format for visualisation.",
journal = "bioRxiv",
year = 2020,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{ORourke1982-bb,
title = "A new linear algorithm for intersecting convex polygons",
author = "O'Rourke, Joseph and Chien, Chi Bin and Olson, Thomas and Naddor,
David",
abstract = "An algorithm is presented that computes the intersection of two
convex polygons in linear time. The algorithm is fundamentally
different from the only known linear algorithms for this problem,
due to Shamos and Hoey. These algorithms depend on a division of
the plane into either angular sectors (Shamos) or parallel slabs
(Hoey), and are mildly complex. Our algorithm searches for the
intersection points of the polygons by adbancing a single pointer
around each polygon, and is very easy to program. \copyright{}
1982.",
journal = "Computer Graphics and Image Processing",
year = 1982,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Barber1996-mj,
title = "The Quickhull Algorithm for Convex Hulls",
author = "Barber, C Bradford and Dobkin, David P and Huhdanpaa, Hannu",
abstract = "The convex hull of a set of points is the smallest convex set
that contains the points. This article presents a practical
convex hull algorithm that combines the two-dimensional Quickhull
Algorithm with the general-dimension Beneath-Beyond Algorithm. It
is similar to the randomized, incremental algorithms for convex
hull and Delaunay triangulation. We provide empirical evidence
that the algorithm runs faster when the input contains nonextreme
points and that it uses less memory. Computational geometry
algorithms have traditionally assumed that input sets are well
behaved. When an algorithm is implemented with floating-point
arithmetic, this assumption can lead to serious errors. We
briefly describe a solution to this problem when computing the
convex hull in two, three, or four dimensions. The output is a
set of ``thick'' facets that contain all possible exact convex
hulls of the input. A variation is effective in five or more
dimensions.",
journal = "ACM Trans. Math. Softw.",
year = 1996,
keywords = "Algorithms; Convex hull; Delaunay triangulation; Halfspace
intersection; I.3.5 [Computer Graphics]: Computational Geometry;
Reliability; Voronoi diagram;Mendeley Import (Feb 23)"
}
@ARTICLE{Han2018-om,
title = "Mapping the Mouse Cell Atlas by {Microwell-Seq}",
author = "Han, Xiaoping and Wang, Renying and Zhou, Yincong and Fei,
Lijiang and Sun, Huiyu and Lai, Shujing and Saadatpour, Assieh
and Zhou, Zimin and Chen, Haide and Ye, Fang and Huang, Daosheng
and Xu, Yang and Huang, Wentao and Jiang, Mengmeng and Jiang,
Xinyi and Mao, Jie and Chen, Yao and Lu, Chenyu and Xie, Jin and
Fang, Qun and Wang, Yibin and Yue, Rui and Li, Tiefeng and Huang,
He and Orkin, Stuart H and Yuan, Guo Cheng and Chen, Ming and
Guo, Guoji",
abstract = "Single-cell RNA sequencing (scRNA-seq) technologies are poised to
reshape the current cell-type classification system. However, a
transcriptome-based single-cell atlas has not been achieved for
complex mammalian systems. Here, we developed Microwell-seq, a
high-throughput and low-cost scRNA-seq platform using simple,
inexpensive devices. Using Microwell-seq, we analyzed more than
400,000 single cells covering all of the major mouse organs and
constructed a basic scheme for a mouse cell atlas (MCA). We
reveal a single-cell hierarchy for many tissues that have not
been well characterized previously. We built a web-based
``single-cell MCA analysis'' pipeline that accurately defines
cell types based on single-cell digital expression. Our study
demonstrates the wide applicability of the Microwell-seq
technology and MCA resource. Development of Microwell-seq allows
construction of a mouse cell atlas at the single-cell level with
a high-throughput and low-cost platform.",
journal = "Cell",
year = 2018,
keywords = "Microwell-seq; cell type classification; cellular heterogeneity;
cross-tissue cellular network; mammalian cell map; mouse cell
atlas; scMCA analysis; single cell RNA-seq; single-cell analysis;
transcriptome analysis;Mendeley Import (Feb 23)"
}
@ARTICLE{Cao2019-po,
title = "The single-cell transcriptional landscape of mammalian
organogenesis",
author = "Cao, Junyue and Spielmann, Malte and Qiu, Xiaojie and Huang,
Xingfan and Ibrahim, Daniel M and Hill, Andrew J and Zhang, Fan
and Mundlos, Stefan and Christiansen, Lena and Steemers, Frank J
and Trapnell, Cole and Shendure, Jay",
abstract = "Mammalian organogenesis is a remarkable process. Within a short
timeframe, the cells of the three germ layers transform into an
embryo that includes most of the major internal and external
organs. Here we investigate the transcriptional dynamics of mouse
organogenesis at single-cell resolution. Using single-cell
combinatorial indexing, we profiled the transcriptomes of around
2 million cells derived from 61 embryos staged between 9.5 and
13.5 days of gestation, in a single experiment. The resulting
`mouse organogenesis cell atlas' (MOCA) provides a global view of
developmental processes during this critical window. We use
Monocle 3 to identify hundreds of cell types and 56 trajectories,
many of which are detected only because of the depth of cellular
coverage, and collectively define thousands of corresponding
marker genes. We explore the dynamics of gene expression within
cell types and trajectories over time, including focused analyses
of the apical ectodermal ridge, limb mesenchyme and skeletal
muscle.",
journal = "Nature",
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
@MISC{Gray_Camp2019-lj,
title = "Mapping human cell phenotypes to genotypes with single-cell
genomics",
author = "Gray Camp, J and Platt, Randall and Treutlein, Barbara",
abstract = "The cumulative activity of all of the body's cells, with their
myriad interactions, life histories, and environmental
experiences, gives rise to a condition that is distinctly human
and specific to each individual. It is an enduring goal to
catalog our human cell types, to understand how they develop, how
they vary between individuals, and how they fail in disease.
Single-cell genomics has revolutionized this endeavor because
sequencing-based methods provide a means to quantitatively
annotate cell states on the basis of high-information content and
high-throughput measurements. Together with advances in stem cell
biology and gene editing, we are in the midst of a fascinating
journey to understand the cellular phenotypes that compose human
bodies and how the human genome is used to build and maintain
each cell. Here, we will review recent advances into how
single-cell genomics is being used to develop personalized
phenotyping strategies that cross subcellular, cellular, and
tissue scales to link our genome to our cumulative cellular
phenotypes.",
journal = "Science",
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Ahrlund-Richter2019-fm,
title = "A whole-brain atlas of monosynaptic input targeting four
different cell types in the medial prefrontal cortex of the mouse",
author = "{\"A}hrlund-Richter, Sofie and Xuan, Yang and van Lunteren,
Josina Anna and Kim, Hoseok and Ortiz, Cantin and Pollak Dorocic,
Iskra and Meletis, Konstantinos and Carl{\'e}n, Marie",
abstract = "The local and long-range connectivity of cortical neurons are
considered instrumental to the functional repertoire of the
cortical region in which they reside. In cortical networks,
distinct cell types build local circuit structures enabling
computational operations. Computations in the medial prefrontal
cortex (mPFC) are thought to be central to cognitive operation,
including decision-making and memory. We used a retrograde
trans-synaptic rabies virus system to generate brain-wide maps of
the input to excitatory neurons as well as three inhibitory
interneuron subtypes in the mPFC. On the global scale the input
patterns were found to be mainly cell type independent, with
quantitative differences in key brain regions, including the
basal forebrain. Mapping of the local mPFC network revealed high
connectivity between the different subtypes of interneurons. The
connectivity mapping gives insight into the information that the
mPFC processes and the structural architecture underlying the
mPFC's unique functions.",
journal = "Nat. Neurosci.",
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Spark2020-hl,
title = "{vLUME}: {3D} Virtual Reality for Single-molecule Localization
Microscopy",
author = "Spark, Alexander and Kitching, Alexandre and Esteban-ferrer,
Daniel and Handa, Anoushka and Carr, Alexander R and Needham,
Lisa-Maria and Ponjavic, Aleks and Da Cunha Santos, Mafalda and
Mccoll, James and Leterrier, Christophe and Davis, Simon J and
Henriques, Ricardo and Lee, Steven F and Alexander, R and
Needham, Lisa-Maria and Ponjavic, Aleks and Da, Mafalda and
Santos, Cunha and Mccoll, James and Davis, Simon J and Henriques,
Ricardo and Lee, Steven F",
abstract = "Super-Resolution (SR) Microscopy based on 3D Single-Molecule
Localization Microscopy (SMLM) is now well established and its
wide-spread adoption has led to the development of more than 36
software packages, dedicated to quantitative evaluation of the
spatial and temporal detection of fluorophore photoswitching.
While the initial emphasis in the 3D SMLM field has clearly been
on improving resolution and data quality, there is now a marked
absence of 3D visualization approaches that enable the
straightforward, high-fidelity exploration of this type of data.
Inspired by the horological phosphorescence points that
illuminate watch-faces in the dark, we present vLUME
(Visualization of the Universe in a Micro Environment, pronounced
'volume') a free-for-academic-use immersive virtual reality-based
(VR) visualization software package purposefully designed to
render large 3D-SMLM data sets. vLUME enables robust
visualization, segmentation and quantification of millions of
fluorescence puncta from any 3D SMLM technique. vLUME has an
intuitive user-interface and is compatible with all commercial VR
hardware (Oculus Rift/Quest and HTC Vive). vLUME accelerates the
analysis of highly complex 3D point-cloud data and the rapid
identification of defects that are otherwise neglected in global
quality metrics.",
journal = "bioRxiv",
year = 2020,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Hu2020-ew,
title = "{ZipSeq} : Barcoding for Real-time Mapping of Single Cell
Transcriptomes",
author = "Hu, Kenneth H and Eichorst, John P and McGinnis, Christopher S
and Patterson, David M and Chow, Eric D and Kersten, Kelly and
Jameson, Stephen C and Gartner, Zev Jordan and Rao, Arjun A and
Krummel, Matthew F",
abstract = "Spatial transcriptomics seeks to integrate single-cell
transcriptomic data within the 3-dimensional space of
multicellular biology. Current methods use glass substrates
pre-seeded with matrices of barcodes or fluorescence
hybridization of a limited number of probes. We developed an
alternative approach, called ZipSeq, that uses patterned
illumination and photocaged oligonucleotides to serially print
barcodes (Zipcodes) onto live cells within intact tissues, in
real-time and with on-the-fly selection of patterns. Using
ZipSeq, we mapped gene expression in three settings: in-vitro
wound healing, live lymph node sections and in a live tumor
microenvironment (TME). In all cases, we discovered new gene
expression patterns associated with histological structures. In
the TME, this demonstrated a trajectory of myeloid and T cell
differentiation, from periphery inward. A variation of ZipSeq
efficiently scales to the level of single cells, providing a
pathway for complete mapping of live tissues, subsequent to
real-time imaging or perturbation.",
journal = "bioRxiv",
pages = "2020.02.04.932988",
month = jan,
year = 2020,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Winnubst2019-mg,
title = "Reconstruction of 1,000 Projection Neurons Reveals New Cell Types
and Organization of {Long-Range} Connectivity in the Mouse Brain",
author = "Winnubst, Johan and Bas, Erhan and Ferreira, Tiago A and Wu,
Zhuhao and Economo, Michael N and Edson, Patrick and Arthur, Ben
J and Bruns, Christopher and Rokicki, Konrad and Schauder, David
and Olbris, Donald J and Murphy, Sean D and Ackerman, David G and
Arshadi, Cameron and Baldwin, Perry and Blake, Regina and
Elsayed, Ahmad and Hasan, Mashtura and Ramirez, Daniel and Dos
Santos, Bruno and Weldon, Monet and Zafar, Amina and Dudman,
Joshua T and Gerfen, Charles R and Hantman, Adam W and Korff,
Wyatt and Sternson, Scott M and Spruston, Nelson and Svoboda,
Karel and Chandrashekar, Jayaram",
abstract = "An efficient pipeline for brain-wide imaging and morphological
reconstruction of individual neurons, including long-range
projection neurons, is presented along with a searchable database
containing more than 1,000 fully reconstructed neurons in the
mouse neocortex, hippocampus, thalamus, and hypothalamus.",
journal = "Cell",
year = 2019,
keywords = "automated reconstruction; axonal morphology; long-range
projections; morphology database; neuronal cell types; neuronal
connectivity; projection neurons; single-cell reconstruction;
whole brain;Mendeley Import (Feb 23)"
}
@ARTICLE{Ortiz2019-oy,
title = "Molecular Atlas of the Adult Mouse Brain",
author = "Ortiz, Cantin and Navarro, Jose Fernandez and Jurek, Aleksandra
and M{\"a}rtin, Antje and Lundeberg, Joakim and Meletis,
Konstantinos",
abstract = "Brain maps are essential for integrating information and
interpreting the structure-function relationship of circuits and
behavior. We aimed to generate a systematic classification of the
adult mouse brain organization based on unbiased extraction of
spatially-defining features. Applying whole-brain spatial
transcriptomics, we captured the gene expression signatures to
define the spatial organization of molecularly discrete
subregions. We found that the molecular code contained
sufficiently detailed information to directly deduce the complex
spatial organization of the brain. This unsupervised molecular
classification revealed new area- and layer-specific subregions,
for example in isocortex and hippocampus, and a new division of
striatum. The whole-brain molecular atlas further supports the
identification of the spatial origin of single neurons using
their gene expression profile, and forms the foundation to define
a minimal gene set - a brain palette -- that is sufficient to
spatially annotate the adult brain. In summary, we have
established a new molecular atlas to formally define the identity
of brain regions, and a molecular code for mapping and targeting
of discrete neuroanatomical domains.",
journal = "bioRxiv",
pages = "784181",
month = jan,
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Asp2019-zh,
title = "A Spatiotemporal {Organ-Wide} Gene Expression and Cell Atlas of
the Developing Human Heart",
author = "Asp, Michaela and Giacomello, Stefania and Larsson, Ludvig and
Wu, Chenglin and F{\"u}rth, Daniel and Qian, Xiaoyan and
W{\"a}rdell, Eva and Custodio, Joaquin and Reimeg{\aa}rd, Johan
and Salm{\'e}n, Fredrik and {\"O}sterholm, Cecilia and
St{\aa}hl, Patrik L and Sundstr{\"o}m, Erik and {\AA}kesson,
Elisabet and Bergmann, Olaf and Bienko, Magda and
M{\aa}nsson-Broberg, Agneta and Nilsson, Mats and Sylv{\'e}n,
Christer and Lundeberg, Joakim",
abstract = "The process of cardiac morphogenesis in humans is incompletely
understood. Its full characterization requires a deep
exploration of the organ-wide orchestration of gene expression
with a single-cell spatial resolution. Here, we present a
molecular approach that reveals the comprehensive
transcriptional landscape of cell types populating the embryonic
heart at three developmental stages and that maps
cell-type-specific gene expression to specific anatomical
domains. Spatial transcriptomics identified unique gene profiles
that correspond to distinct anatomical regions in each
developmental stage. Human embryonic cardiac cell types
identified by single-cell RNA sequencing confirmed and enriched
the spatial annotation of embryonic cardiac gene expression. In
situ sequencing was then used to refine these results and create
a spatial subcellular map for the three developmental phases.
Finally, we generated a publicly available web resource of the
human developing heart to facilitate future studies on human
cardiogenesis.",
journal = "Cell",
publisher = "Cell Press",
volume = 179,
number = 7,
pages = "1647--1660.e19",
month = dec,
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Moon2017-pz,
title = "{PHATE}: A Dimensionality Reduction Method for Visualizing
Trajectory Structures in {High-Dimensional} Biological Data",
author = "Moon, Kevin R and van Dijk, David and Wang, Zheng and Chen,
William and Hirn, Matthew J and Coifman, Ronald R and Ivanova,
Natalia B and Wolf, Guy and Krishnaswamy, Smita",
abstract = "In recent years, dimensionality reduction methods have become
critical for visualization, exploration, and interpretation of
high-throughput, high-dimensional biological data, as they enable
the extraction of major trends in the data while discarding
noise. However, biological data contains a type of predominant
structure that is not preserved in commonly used methods such as
PCA and tSNE, namely, branching progression structure. This
structure, which is often non-linear, arises from underlying
biological processes such as differentiation, graded responses to
stimuli, and population drift, which generate cellular (or
population) diversity. We propose a novel, affinity-preserving
embedding called PHATE (Potential of Heat-diffusion for
Affinity-based Trajectory Embedding), designed explicitly to
preserve progression structure in data. PHATE provides a
denoised, two or three-dimensional visualization of the complete
branching trajectory structure in high-dimensional data. It uses
heat-diffusion processes, which naturally denoise the data, to
compute cell-cell affinities. Then, PHATE creates a
diffusion-potential geometry by free-energy potentials of these
processes. This geometry captures high-dimensional trajectory
structures, while enabling a natural embedding of the intrinsic
data geometry. This embedding accurately visualizes trajectories
and data distances, without requiring strict assumptions
typically used by path-finding and tree-fitting algorithms, which
have recently been used for pseudotime orderings or
tree-renderings of cellular data. Furthermore, PHATE supports a
wide range of data exploration tasks by providing interpretable
overlays on top of the visualization. We show that such overlays
can emphasize and reveal trajectory end-points, branch points and
associated split-decisions, progression-forming variables (e.g.,
specific genes), and paths between developmental events in
cellular state-space. We demonstrate PHATE on single-cell RNA
sequencing and mass cytometry data pertaining to embryoid body
differentiation, IPSC reprogramming, and hematopoiesis in the
bone marrow. We also demonstrate PHATE on non-single cell data
including single-nucleotide polymorphism (SNP) measurements of
European populations, and 16s sequencing of gut microbiota.",
journal = "bioRxiv",
year = 2017,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Bergen2019-vm,
title = "Generalizing {RNA} velocity to transient cell states through
dynamical modeling",
author = "Bergen, Volker and Lange, Marius and Peidli, Stefan and Wolf, F
Alexander and Theis, Fabian J",
abstract = "The introduction of RNA velocity in single cells has opened up
new ways of studying cellular differentiation. The originally
proposed framework obtains velocities as the deviation of the
observed ratio of spliced and unspliced mRNA from an inferred
steady state. Errors in velocity estimates arise if the central
assumptions of a common splicing rate and the observation of the
full splicing dynamics with steady-state mRNA levels are
violated. With scVelo (), we address these restrictions by
solving the full transcriptional dynamics of splicing kinetics
using a likelihood-based dynamical model. This generalizes RNA
velocity to a wide variety of systems comprising transient cell
states, which are common in development and in response to
perturbations. We infer gene-specific rates of transcription,
splicing and degradation, and recover the latent time of the
underlying cellular processes. This latent time represents the
cell's internal clock and is based only on its transcriptional
dynamics. Moreover, scVelo allows us to identify regimes of
regulatory changes such as stages of cell fate commitment and,
therein, systematically detects putative driver genes. We
demonstrate that scVelo enables disentangling heterogeneous
subpopulation kinetics with unprecedented resolution in
hippocampal dentate gyrus neurogenesis and pancreatic
endocrinogenesis. We anticipate that scVelo will greatly
facilitate the study of lineage decisions, gene regulation, and
pathway activity identification.",
journal = "bioRxiv",
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Melsted2019-nf,
title = "Modular and efficient pre-processing of single-cell {RNA-seq}",
author = "Melsted, P{\'a}ll and Booeshaghi, A Sina and Gao, Fan and
Beltrame, Eduardo and Lu, Lambda and Hjorleifsson, Kristj{\'a}n
Eldj{\'a}rn and Gehring, Jase and Pachter, Lior",
abstract = "Analysis of single-cell RNA-seq data begins with pre-processing
of sequencing reads to generate count matrices. We investigate
algorithm choices for the challenges of pre-processing, and
describe a workflow that balances efficiency and accuracy. Our
workflow is based on the kallisto () and bustools () programs,
and is near-optimal in speed and memory. The workflow is modular,
and we demonstrate its flexibility by showing how it can be used
for RNA velocity analyses. Documentation and tutorials for using
the kallisto | bus workflow are available at .",
journal = "bioRxiv",
year = 2019,
keywords = "Mendeley Import (Feb 23)"
}
@ARTICLE{Popescu2019-zg,
title = "Decoding human fetal liver haematopoiesis",
author = "Popescu, Dorin-Mirel and Botting, Rachel A and Stephenson, Emily
and Green, Kile and Webb, Simone and Jardine, Laura and
Calderbank, Emily F and Polanski, Krzysztof and Goh, Issac and
Efremova, Mirjana and Acres, Meghan and Maunder, Daniel and Vegh,
Peter and Gitton, Yorick and Park, Jong-Eun and Vento-Tormo,
Roser and Miao, Zhichao and Dixon, David and Rowell, Rachel and
McDonald, David and Fletcher, James and Poyner, Elizabeth and
Reynolds, Gary and Mather, Michael and Moldovan, Corina and
Mamanova, Lira and Greig, Frankie and Young, Matthew D and Meyer,
Kerstin B and Lisgo, Steven and Bacardit, Jaume and Fuller,
Andrew and Millar, Ben and Innes, Barbara and Lindsay, Susan and
Stubbington, Michael J T and Kowalczyk, Monika S and Li, Bo and
Ashenberg, Orr and Tabaka, Marcin and Dionne, Danielle and
Tickle, Timothy L and Slyper, Michal and Rozenblatt-Rosen, Orit
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and Behjati, Sam and Laurenti, Elisa and Teichmann, Sarah A and