Update human_pathogen_genomics.md

* Improving the page style. 
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pages/your_domain/human_pathogen_genomics.md

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 ## Introduction
 The human pathogen genomics domain focuses on studying the genetic code of organisms that cause disease in humans. Studies to identify and understand pathogens are conducted across different types of organisations ranging from research institutes to regional public health authorities. The aims can include urgent outbreak response, prevention measures, and developing remedies such as treatments and vaccines.
 
-Data management challenges in this domain include the potential urgency of data sharing and secondary use of data across initiatives emerging from research, public health and policy. While the pathogenic organisms are the object of interest, there are many considerations to account for when dealing with samples collected from patients, pathogen surveillance, and human research subjects.
+Data management challenges in this domain include the potential urgency of data sharing and secondary use of data across initiatives emerging from research, public health and policy. While the pathogenic organisms are the object of interest, there are many considerations to take into account when dealing with samples collected from patients, pathogen surveillance, and human research subjects.
 
-The genomic data can represent anything from the genetic sequence of a single pathogen isolate to various fragments of genetic materials from a flora of pathogens in larger population. Other data can represent a wide range of contextual information about the human host, the disease, and various environmental factors.
+The genomic data can represent anything from the genetic sequence of a single pathogen isolate to various fragments of genetic materials from a flora of pathogens in a larger population. Other data can represent a wide range of contextual information about the human host, the disease, and various environmental factors.
 
 ## Planning a study with pathogen genomic data
 
 ### Description
-While the object of interest in this domain are pathogens, the data is usually derived from samples originating from patients and human research subjects. This means that you must plan to either remove or to handle [human data](human_data) during your study.
+While the objects of interest in this domain are pathogens, the data is usually derived from samples originating from patients and human research subjects. This means that you must plan to either remove or handle [human data](human_data) during your study.
 
 ### Considerations
 
@@ -35,12 +35,12 @@ While the object of interest in this domain are pathogens, the data is usually d
   * What is the appropriate scope for the legal and ethical agreements necessary for the study?
   * How should statements related to data processing be phrased to allow timely and efficient data sharing?
   * How much time would be required to negotiate access to the samples and data for the study?
-* What public health and research initives should you consider aligning with?
+* What public health and research initiatives should you consider aligning with?
   * What data could be shared with or reused from other initiatives during the project?
   * How will you align your practices with these initiatives to maximise the impact of the data and insight generated by the project? 
   * How will you share data with your collaborators and other initiatives?
 * What conventions will you adopt when planning your study?
-  * What existing protocols should you consider adopting for sample preparation, sequencing, variant calling etc? 
+  * What existing protocols should you consider adopting for operations such as sample preparation, sequencing, and variant calling? 
   * What conventions should you adopt for documenting your research? 
 
 ### Solutions
@@ -51,10 +51,10 @@ While the object of interest in this domain are pathogens, the data is usually d
   * [Processing and analysing human data](human_data#processing-and-analysing-human-data)
 
 #### Isolate pathogen from host information
-* Depending on the pathogen, how it interacts with the host, or the methods applied, it can be possible to generate clean isolates that do not contain host related material. Data produced from a clean isolate could potentially be handled with few restrictions, while other data will be considered to be personal and [sensitive](data_sensitivity) that need [protection](data_security).
+* Depending on the pathogen and how it interacts with the host or the methods applied, it can be possible to generate clean isolates that do not contain host-related material. Data produced from a clean isolate could potentially be handled with few restrictions, while other data will be considered to be personal and [sensitive](data_sensitivity) and will need [protection](data_security).
 
 #### Public health initiatives
-* National and international recommendations from public health authorities, epidemic surveillance programs and research data communities should be considered when planning a new study or surveillance programme. In particular, you could consult conventions for relevant surveillance programs while considering widely adopted guidelines for research documentation, and instructions from the data sharing platforms.
+* National and international recommendations from public health authorities, epidemic surveillance programs and research data communities should be considered when planning a new study or surveillance programme. In particular, you could consult conventions for relevant surveillance programs while considering widely adopted guidelines for research documentation, and instructions from the data-sharing platforms.
   * [European Centre for Disease Prevention and Control (ECDC)](https://www.ecdc.europa.eu/en) coordinates [Disease and laboratory networks](https://www.ecdc.europa.eu/en/about-ecdc/what-we-do/partners-and-networks/disease-and-laboratory-networks) and also issues [Surveillance and reporting protocols](https://www.ecdc.europa.eu/en/search?s=protocol) and other [Technical guidance on sequencing](https://www.ecdc.europa.eu/en/search?s=protocol).
   * [WHO genomic surveillance strategy](https://www.who.int/initiatives/genomic-surveillance-strategy) and [guidance on implementation for maximum impact on public health](https://apps.who.int/iris/handle/10665/338480) and there are published reports that advise on [Implementing Quality Management Systems in Public Health Laboratories](https://doi.org/10.1128/jcm.00261-19).
   * The US Centers for Disease Control and Prevention (CDC) offers guidance on [Pathogen genomics](https://www.cdc.gov/genomics/pathogen/index.htm) for its work in monitoring, investigating, and controlling infectious diseases.
@@ -65,7 +65,7 @@ While the object of interest in this domain are pathogens, the data is usually d
   * Adopt recommendations specifically for genomics and pathogen genomics such as [Ten simple rules for annotating sequencing experiments](https://doi.org/10.1371/journal.pcbi.1008260).
   * Refer to general guidance on how to provide [documentation and metadata](metadata_management) during your project.
 * Adopt standards, conventions and robust protocols to maximise the reuse potential of the data in parallel initiatives and your future projects.
-  * The Genomic Standards Consortium (GSC) develops and maintains the [GSC Minimum Information about any Sequence (MIxS)](https://fairsharing.org/FAIRsharing.9aa0zp) set of core and extended descriptors for genomes and metagenomes with associated samples and their environment to guide scientists on how to capture the metadata essential for high quality research. 
+  * The Genomic Standards Consortium (GSC) develops and maintains the {% tool "mixs" %} and the {% tool "migs-mims" %}set of core and extended descriptors for genomes and metagenomes with associated samples and their environment to guide scientists on how to capture the metadata essential for high-quality research. 
   * The GenEpiO Consortium develops and maintains the [Genomic Epidemiology Application Ontology (GenEpiO)](https://doi.org/10.25504/FAIRsharing.y1mmbv) to support data sharing and integration specifically for foodborne infectious disease surveillance and outbreak investigations.
   * The [Public Health Alliance for Genomic Epidemiology (PHA4GE)](https://pha4ge.org/) supports openness and interoperability in public health bioinformatics. The [Data Structures working group](https://pha4ge.org/working-groups/) develops, adapts and standardises data models for microbial sequence data, contextual metadata, results and workflow metrics, such as the [SARS-CoV-2 contextual data specification](https://github.com/pha4ge/SARS-CoV-2-Contextual-Data-Specification).
   * ISO (the International Organization for Standardization) has issued standards that can be referenced when designing or commissioning genomic sequencing and informatics services, such as