Render course

docs/01-intro.md

@@ -40,7 +40,7 @@ Informatics work presents unique challenges due to the fact that it requires mul
 
 According to a recent article about this subject:
 
-> "Computational biology hinges on mutual respect between researchers from different disciplines, and a key element of respect is understand a colleague's particular expertise." [carpenter_cultivating_2021]
+> "Computational biology hinges on mutual respect between scientists from different disciplines, and key elements of respect are understanding a colleague’s particular expertise and motivation." [way_field_2021]
 
 
 In this course we hope to give you a bit more of an understanding of the variety of perspectives that your colleagues might have.

docs/02-team_guidelines.md

@@ -68,11 +68,15 @@ Finally, you also want to look for individuals who seem to get things done. You
 Be careful about assuming that your experimental collaborator can do any type of wet bench experiment or that your informatics collaborator can analyze any type of data.
 
 
-> "Computational biology hinges on mutual respect between researchers from different disciplines, and a key element of respect is understanding a colleague’s particular expertise" [@carpenter_cultivating_2021].
+> "Computational biology hinges on mutual respect between researchers from different disciplines, and a key element of respect is understanding a colleague’s particular expertise" [@way_field_2021].
+
+> "Computationalists do not like to be seen as “just” running the numbers any more than biologists appreciate the perception that they are “just” a pair of hands that produced the data" [@way_field_2021].
+
+> "Statistics, database structures, clinical informatics, genetics, epigenetics, genomics, proteomics, imaging, single-cell technologies, structure prediction, algorithm development, machine learning, and mechanistic modeling are all distinct fields. Biologists should not be offended if a particular idea does not fit a computational biologist’s research agenda, and computational scientists need to clearly communicate analysis considerations, approaches, and limitations" [@way_field_2021].
+
+> "Certain grant mechanisms can provide flexibility for computational biologists to develop new technologies, but the scope often focuses on method development, limiting the ability to collaborate on application-oriented projects. The current academic systems incentivize mechanism and translational discovery for biology but methodological or theoretical advances for computational sciences. This explains a common disconnect when collaborating: **Projects that require routine use of existing methodology typically provide little benefit to the computational person’s academic record no matter how unique a particular dataset.**" [@way_field_2021]
 
-> "Computationalists do not like to be seen as “just” running the numbers any more than biologists appreciate the perception that they are “just” a pair of hands that produced the data" [@carpenter_cultivating_2021].
 
-> "Statistics, database structures, clinical informatics, genetics, epigenetics, genomics, imaging, single-cell technologies, structure prediction, algorithm development, machine learning, and mechanistic modeling are all distinct fields. Biologists should not be offended if a particular collaboration idea does not fit a computational biologist’s research agenda or expertise...a computational biologist’s research laboratory often must focus on novel methods development in a particular area for career advancement" [@carpenter_cultivating_2021].
 
 ## Communication for informatics teams
 

docs/04-informatics_relationships.md

@@ -107,11 +107,11 @@ Sharing and discussing budget information early and often can help research memb
 
 It is also important to recognize that:
 
-> "There is a common misconception that the lack of physical experimentation and laboratory supplies makes analysis work automated, quick, and inexpensive" [@carpenter_cultivating_2021].
+> "There is a common misconception that the lack of physical experimentation and laboratory supplies makes computational work automated, quick, and inexpensive." [@way_field_2021].
 
 However:
 
-> "In reality, even for well-established data types, analysis can often take **as much or more time** and effort to perform as generating the data at the bench. Moreover, it typically also requires pipeline optimization, software development and maintenance, and user interfaces so that methods remain usable beyond the scope of a single publication or project" [@carpenter_cultivating_2021].
+> "In reality, even for well-established data types, analysis can often take **as much or more time** and effort to perform as generating the data at the bench. Moreover, it typically also requires pipeline optimization, software development and maintenance, and user interfaces so that methods remain usable beyond the scope of a single publication or project" [@way_field_2021].
 
 Don't forget to provide some budget for your informatics collaborators, as their time ultimately does cost money and there may be computational costs that you may not be aware of. 
 
@@ -234,7 +234,7 @@ Wherever possible also try to advocate for more nuanced academic promotion polic
 
 For your students who wish to stay in academia, it may be less important that they become as generally familiar with a wide variety of data science skills and practices as students interested in a career outside of academia, if they are for example focusing on a specific statistical method. Just like other academic fields, informatics experts will become experts in niche subject areas. Encourage these students to go to targeted conferences to build a network in their field of interest (although we still encourage if possible to allow your students to get a well-rounded exposure to different types of conferences). Also especially encourage these students to learn about grantsmanship just as you would with your other academic mentees. However this can also be useful for students interested in working for a nonprofit or for the government. 
 
-See @carpenter_cultivating_2021 and @waller_documenting_2018 for a more in-depth discussion and suggestions on how we can work to reform academic promotion practices to be more mindful of disciplinary differences for informatics experts.
+See @way_field_2021 and @waller_documenting_2018 for a more in-depth discussion and suggestions on how we can work to reform academic promotion practices to be more mindful of disciplinary differences for informatics experts.
 
 
 #### Authorship considerations

docs/05-promoting_diversity.md

@@ -59,7 +59,7 @@ Many Black scientists are responsible for great human achievements that changed
 
 - [Vivien Thomas (1910–1985)](https://en.wikipedia.org/wiki/Vivien_Thomas): Vivien was a pioneer in [heart surgery at Johns Hopkins](https://www.hopkinsmedicine.org/som/giving/vtfund.html) in the 1940s when it was considered taboo. He is credited for assisting in creating a life saving surgical operation that improved the oxygenation of children with congenital heart defects. This operation was pivotal in paving the way for other heart surgical procedures. Sadly, it took more than 25 years for him to be credited for this work.
 
-See [this article for more information about Katherine Johnson and other pioneering and world-changing Black female  scientsist](https://www.biography.com/scientists/katherine-johnson-black-female-science-technology-engineering-mathematics). Also check out this [list of inspiring Black scientists today ](http://crosstalk.cell.com/blog/100-inspiring-black-scientists-in-america).
+See [this article for more information about Katherine Johnson and other pioneering and world-changing Black female  scientists](https://www.biography.com/scientists/katherine-johnson-black-female-science-technology-engineering-mathematics). Also check out this [list of inspiring Black scientists today ](http://crosstalk.cell.com/blog/100-inspiring-black-scientists-in-america).
 
 Scientists and mathematicians of Latin American or Hispanic origin have also greatly contributed and continue to contribute to scientific innovation:
 
@@ -198,7 +198,7 @@ In a study of clinical trial participants of marginalized groups, participants s
 
 > "In addition, participants noted that the enthusiasm, commitment, or passion of the researcher to help the population of interest and to study the topic of interest influenced how trustworthy the researcher appeared to be" [@griffith_determinants_2020].
 
-Participants also state that the feel more trusting and more willing to participant in trials with a researcher of a similar background. Thus, improving the diversity of research teams and supporting underrepresented investigators may help to recruit more diverse participants for clinical trials [@ACRP_representation_2020]. In addition, [culture competency training](https://www.cigna.com/health-care-providers/resources/cultural-competency-training) and [Diversity, Equity, and Inclusion (DEI) training](https://www.diversityinclusiontraining.com/) can help! See [here](https://www.samhsa.gov/section-223/cultural-competency/resources) for additional cultural competency training resources.
+Participants also state that they feel more trusting and more willing to participant in trials with a researcher of a similar background. Thus, improving the diversity of research teams and supporting underrepresented investigators may help to recruit more diverse participants for clinical trials [@ACRP_representation_2020]. In addition, [culture competency training](https://www.cigna.com/health-care-providers/resources/cultural-competency-training) and [Diversity, Equity, and Inclusion (DEI) training](https://www.diversityinclusiontraining.com/) can help! See [here](https://www.samhsa.gov/section-223/cultural-competency/resources) for additional cultural competency training resources.
 
 ### **Barriers of access**
 

docs/guidelines-for-multidisciplinary-informatics-teams.html

@@ -394,13 +394,16 @@ <h3><span class="header-section-number">2.1.2</span> <strong>Who to look for</st
 <h3><span class="header-section-number">2.1.3</span> <strong>Adjust your expectations</strong><a href="guidelines-for-multidisciplinary-informatics-teams.html#adjust-your-expectations" class="anchor-section" aria-label="Anchor link to header"></a></h3>
 <p>Be careful about assuming that your experimental collaborator can do any type of wet bench experiment or that your informatics collaborator can analyze any type of data.</p>
 <blockquote>
-<p>“Computational biology hinges on mutual respect between researchers from different disciplines, and a key element of respect is understanding a colleague’s particular expertise” <span class="citation">(<a href="#ref-carpenter_cultivating_2021">Carpenter et al. 2021</a>)</span>.</p>
+<p>“Computational biology hinges on mutual respect between researchers from different disciplines, and a key element of respect is understanding a colleague’s particular expertise” <span class="citation">(<a href="#ref-way_field_2021">Way et al. 2021</a>)</span>.</p>
 </blockquote>
 <blockquote>
-<p>“Computationalists do not like to be seen as “just” running the numbers any more than biologists appreciate the perception that they are “just” a pair of hands that produced the data” <span class="citation">(<a href="#ref-carpenter_cultivating_2021">Carpenter et al. 2021</a>)</span>.</p>
+<p>“Computationalists do not like to be seen as “just” running the numbers any more than biologists appreciate the perception that they are “just” a pair of hands that produced the data” <span class="citation">(<a href="#ref-way_field_2021">Way et al. 2021</a>)</span>.</p>
 </blockquote>
 <blockquote>
-<p>“Statistics, database structures, clinical informatics, genetics, epigenetics, genomics, imaging, single-cell technologies, structure prediction, algorithm development, machine learning, and mechanistic modeling are all distinct fields. Biologists should not be offended if a particular collaboration idea does not fit a computational biologist’s research agenda or expertise…a computational biologist’s research laboratory often must focus on novel methods development in a particular area for career advancement” <span class="citation">(<a href="#ref-carpenter_cultivating_2021">Carpenter et al. 2021</a>)</span>.</p>
+<p>“Statistics, database structures, clinical informatics, genetics, epigenetics, genomics, proteomics, imaging, single-cell technologies, structure prediction, algorithm development, machine learning, and mechanistic modeling are all distinct fields. Biologists should not be offended if a particular idea does not fit a computational biologist’s research agenda, and computational scientists need to clearly communicate analysis considerations, approaches, and limitations” <span class="citation">(<a href="#ref-way_field_2021">Way et al. 2021</a>)</span>.</p>
+</blockquote>
+<blockquote>
+<p>“Certain grant mechanisms can provide flexibility for computational biologists to develop new technologies, but the scope often focuses on method development, limiting the ability to collaborate on application-oriented projects. The current academic systems incentivize mechanism and translational discovery for biology but methodological or theoretical advances for computational sciences. This explains a common disconnect when collaborating: <strong>Projects that require routine use of existing methodology typically provide little benefit to the computational person’s academic record no matter how unique a particular dataset.</strong>” <span class="citation">(<a href="#ref-way_field_2021">Way et al. 2021</a>)</span></p>
 </blockquote>
 </div>
 </div>
@@ -550,7 +553,7 @@ <h3><span class="header-section-number">2.4.7</span> <strong>Advocate authorship
 <p>Regardless of your employees’ or students’ backgrounds, make sure you advocate for authorship for each of them (particularly if they are interested in a career in research).</p>
 <p>According to a recent report about computational biology:</p>
 <blockquote>
-<p>“Despite the fact that dramatic advancements have been driven by computational biology, too often researchers choosing this path languish in career advancement, publication, and grant review” <span class="citation">(<a href="#ref-carpenter_cultivating_2021">Carpenter et al. 2021</a>)</span>.</p>
+<p>“Despite the fact that dramatic advancements have been driven by computational biology, too often researchers choosing this path languish in career advancement, publication, and grant review” <span class="citation">(<a href="#ref-carpenter_cultivating_2021"><strong>carpenter_cultivating_2021?</strong></a>)</span>.</p>
 </blockquote>
 <p>It is often overlooked, but informatics experts will also need <strong>first author papers</strong>. However, keep in mind that in some fields authors are listed in different ways.</p>
 <p>Allow your employees to <strong>generate ideas</strong> for such publications and discuss this with them. Often the work to help with other projects may not be as interesting for your employee as an idea that they come up with themselves.</p>
@@ -593,9 +596,6 @@ <h3>References<a href="references.html#references" class="anchor-section" aria-l
 <div id="ref-broman_collaborating_2019" class="csl-entry">
 Broman, Karl. 2019. <span>“Collaborating Reproducibly.”</span> <a href="https://www.biostat.wisc.edu/~kbroman/presentations/rrcollab_aaas2019.pdf">https://www.biostat.wisc.edu/~kbroman/presentations/rrcollab_aaas2019.pdf</a>.
 </div>
-<div id="ref-carpenter_cultivating_2021" class="csl-entry">
-Carpenter, Anne E, Casey S Greene, Piero Carninci, Benilton S Cervalho, Michiel de Hoon, Stacey Finley, Jerry SH Lee, et al. 2021. <span>“Cultivating Computational Biology.”</span> <em>arXiv [q-Bio.OT]</em>, 12. <a href="https://doi.org/arXiv:2104.11364">https://doi.org/arXiv:2104.11364</a>.
-</div>
 <div id="ref-haden_5_2014" class="csl-entry">
 Haden, Jeff. 2014. <span>“5 <span>Ways</span> to <span>Ask</span> the <span>Perfect</span> <span>Question</span>.”</span> <em>Inc.com</em>. <a href="https://www.inc.com/jeff-haden/5-ways-to-ask-the-perfect-question.html">https://www.inc.com/jeff-haden/5-ways-to-ask-the-perfect-question.html</a>.
 </div>
@@ -617,6 +617,9 @@ <h3>References<a href="references.html#references" class="anchor-section" aria-l
 <div id="ref-watson_lonely_2014" class="csl-entry">
 ———. 2014. <span>“The Lonely Bioinformatician Revisited: Clinical Labs <span></span>.”</span> <em>Opiniomics.org</em>. <a href="http://www.opiniomics.org/the-lonely-bioinformatician-revisited-clinical-labs/">http://www.opiniomics.org/the-lonely-bioinformatician-revisited-clinical-labs/</a>.
 </div>
+<div id="ref-way_field_2021" class="csl-entry">
+Way, Gregory P., Casey S. Greene, Piero Carninci, Benilton S. Carvalho, Michiel De Hoon, Stacey D. Finley, Sara J. C. Gosline, et al. 2021. <span>“A Field Guide to Cultivating Computational Biology.”</span> <em>PLOS Biology</em> 19 (10): e3001419. <a href="https://doi.org/10.1371/journal.pbio.3001419">https://doi.org/10.1371/journal.pbio.3001419</a>.
+</div>
 </div>
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