White background with navy text that says, "Welcome! Chat with the Chair of Bioinformatics!" Below, a picture of someone working in a lab.
Thomas Screnci: All right. So thank you for joining us for this chat with the chair of Bioinformatics. I am Thomas Screnci, the Associate Director of admissions and enrollment with Brandeis Online. I'll be one of your hosts for this session, and we will jump into our session right now.
So, as mentioned just a second ago. You are free to use the chat feature of this zoom to ask questions throughout the presentation. Do ask you to keep your microphones muted. Just the audio issues are clear. And there are, of course, like I said, Q&A, at the end of the session as well. So please ask questions whenever you feel comfortable. And we'll be happy to answer them.
Screen changes to say "Moderators." Below, headshots and contact info Tom Screnci (tscrenci@brandeis.edu) and Jess Ronan (jronan@brandeis.edu).
Tom Screnci speaks: So I am Tom Screnci. I'm the Associate Director of Admissions and Enrollment for Brandeis Online. My colleague, Jess Ronan, is not here, but she and I make up the admissions team answering any questions for prospective students reading applications, doing anything we can related to questions, applications, enrollment, things like that. You can email us directly through our email account. There, we both regularly check the general email account, online@brandeis.edu, at the bottom of your screen. So please feel free to email any of those 3 email addresses or give us a call, and we're happy to help.
We're joined by our chair. Alan Chang! Alan, thank you for making time for us today. I'll introduce himself. Talk a bit about his background, his current experience, as well.
Powerpoint changes to say "Program Chair." There's a headshot of Alan Cheng, PhD, with bullet points below: Senior Director of Merck & Co, PhD University of California San Francisco, Past roles include: Principal Scientist at Amgen and Senior Scientist at Pfizer.
Alan Cheng speaks: Yeah, good morning, everyone. So I'm Alan Chang. I'm the program chair in bioinformatics. And I've been with Brandeis for almost 20 years, started teaching on campus. And then, as the program moved online, I also moved online and I also moved to San Francisco, where I am. Currently, I'm a senior director at Merck, where I lead a group that does drug discovery and target analysis. You can see my education and some past roles here. Yeah. Excited to meet you.
Thomas Screnci: Excellent.
Slide switches to say "Agenda." Bullet points say: Bioinformatics curriculum, Marketplace information, Admissions info, Open Q&A.
Tom Screnci speaks: Thank you, Alan. So today we're going to go over information to help you make the best decision regarding a master's program or certificate, and we're going to do the best. Answer any questions you have and questions we hear the most often. So today, we're going to be covering overview of the Bioinformatics curriculum for the master's certificate and the Master's degree insights into the bioinformatics field, and of course, covering admissions, questions and time for Q. And at the end, open the floor to any questions you may have, but feel free again to ask questions throughout the presentation. I know I can like to ask questions, as I think in the book before I forget them. So please feel free to do that.
So with that, I'm gonna hand it over a bit to Alan to talk a little bit more about the Brandeis online master's and certificate program. So, Alan, would you please jump into that.
Slide switches to say "Program Defining Features." Four defining features are listed: Statistical and computational methods; Communication of bioinformatics analyses; Biological data analyses; Modeling biological processes to provide new insights.
Alan Cheng speaks: Sure. Yeah. Thank you. Yep, so you can see our program defining features here, and I'll kind of start at the top left corner and then go around the circle. So, of course, for bioinformatics, you are learning computational approaches to computational biology, approaches genomics, approaches a lot of that is based on statistical approaches and the ability to process a fairly large, fairly large data sets to glean insights.
And those methods lead into your biological data analysis. And part of this is understanding the biology, not just, you know, data processing and then being able to interpret that data leading to the modeling biological processes to provide new insights. Basically, you want to take your computational approaches, process the data, understand the relevance of the data, and then provide insights on next experiments to do or conclusions to draw from the data.
And of course, bioinformatics is a multidisciplinary field, and you are often almost always working in teams of people with different levels of understanding of bioinformatics. Sometimes you're communicating with a biologist, sometimes you're communicating with a clinician, sometimes it's it. People or more informatics or technology focused folks. And so communication of your analyses is really important, and we include that throughout our courses things like final project presentations and written reports. Those are pretty key, not just you understanding the bioinformatics, but also be able to communicate that out.
Slide switches to say "Required Courses." Required courses include: RBIF 100 — Bioinformatics Scripting and Databases with Python; RBIF 102 — Molecular Biology, Genetics, and Disease; RBIF 109 — Biological Sequence Analysis; RBIF 111 — Biomedical Statistics with R; RBIF 112 — Mathematical Modeling for Bioinformatics; and RBIF 114 — Molecular Profiling and Biomarker Discovery.
Alan Cheng speaks: And a couple courses well, actually, these are all our courses. So there are a set of required courses, or 6 of them. And these take you through scripting. With RBIF 100, you learn R and RBIF 111, and then you apply it to various bioinformatics tasks in those courses.
102 is a biology background, graduate level molecular biology. It actually includes some R as well. All these courses are crafted specifically for bioinformatics. And so this gives you kind of efficient learning of bioinformatics. But also we you normally wouldn't see our in a molecular biology course. And and so we're able to do things like that, so that the bioinformatics learning is more seamless and more efficient for you.
Sequence Analysis is very key. Of course, that's a lot of a lot of the genomics aspects of bioinformatics. And then 112 is essentially machine learning a lot of different methods for doing machine learning on data and then biomarker discovery, molecular profiling, single cell, RNA-seq proteomics that's in 114, and then on the right side, you have a bunch of electives. So you get to choose 4 of these. And it really, you know, you can be guided by your interests and your you know, future plans, and I'll just point out 2 courses at the bottom. 1 20 is sort of a capstone type project. It's not required to elective. But it's a great way to kind of integrate all the learnings you have throughout the program on a topic that you're really interested in. So we we not all students do this. But we've had a number of students. Do this, and I think they enjoyed it.
290 is just sometimes we offer it as special topics, things that are, you know, pretty current. Or we want to try out a topic. Sometimes we offer this. The last one we had was functional genomics, and that actually went quite well. We rolled in a lot of the material into some of the other courses, so statistical genetics, and some of it into other courses, as well.
Elective courses are displayed on the screen. Courses include: RBIF 101 — Structural Bioinformatics; RBIF 106 — Drug Discovery and Development; RBIF 108 — Computational Systems Biology; RBIF 110 — Cheminformatics; RBIF 115 — Statistical Genetics; RBIF 120 — Research Topics in Computational Biology; and RBIF 290 — Special Topics in Bioinformatics.
Thomas Screnci says: Thank you, Alan. So these are the required elective courses for the Master's degree. We do offer 3 master's certificates as well, and, as you very likely notice all of the courses, for the master's certificates are part of the curriculum for the Master's degree.
Slide changes to display the curriculum for three master's certificates: Cheminformatics, Drug Discovery Informatics, and Genomics.
Tom Screnci speaks: So if you decided to start with a certificate. You could stack any number in any of these 3 certificates into the degree. So with completing these, the 4 courses for your certificate, you would just have 6 remaining courses to earn the Master's degree. So you can do that as a pathway if you so chose, or of course you could just you could go right into the degree. Just do a certificate and move on. It's, of course, up to you. So happy to answer any questions on that. But those are 3 pathways into the degree, but also 3 individual certificate curriculums. We do offer right here.
We also, which is on the newer side, offer a healthcare analytics which does share some courses. So if you're in the healthcare field and wanted to get a more analytical knowledge, move into more analytical fields, maybe move away from from patients. That is another pathway, possibly into bioinformatics in a related field that we do share as well. There is a fast track option for the Master's degree. The fast track is different than our full time tracks for other programs where the fast track is typically a 15 month program, whereas a lot of our full time programs can be completed in a year. The fast track does allow you to complete it in a pretty brief period of time. You can work part time in your degree and do as little as one course per session.
We currently offer 4 sessions a year. Shortly moving to 5 sessions a year, so you could chip away very slowly and do one course at a time, just for your own availability. 98% of our students are working full time. So we are very much used to people who are taking part time courses with busy lives. So that's an important note to also to to include, while I talk about the certificates, the pathways we do offer here. So with that I'll hand it back to Alan. If you wouldn't mind jumping into talking a little bit more about some required courses for bioinformatics. Please.
Slide switches to say "Required Course." Heading says RBIF 100: "Bioinformatics Scripting and Databases with Python." Bullet points below say: "A high-content introduction to scripting and programming with applications in bioinformatics. Appropriate for students with little previous programming experience. Course covers fundamentals of working with Linux systems, using bioinformatics tools, and manipulating biological data files. The focus will be on scripting with Bash and Python."
Alan Cheng speaks: Yeah. So I mentioned our BIF 100 when we looked at all the courses. This is one of the 1st courses that you'll be taking. So 100 or 102, and in this course you pick up scripting. So it's like shell scripting as well as python coding, and you apply it directly into bioinformatics, tasks, bringing in data doing some simple analyses on sequences. And it's a great way to jump into coding. Learn about Linux systems use tools and start looking at biological data, and we don't require any programming experience coming in. However, I would say that it is helpful to have done some tutorials.
It'll just make your life easier when you take the course, and Brandeis actually offers some tutorials, usually right before the course, highly highly encourage you to take those opportunities they're offered in conjunction with the Brandeis Library. It's usually one or 2 sessions so highly encourage you to do that before before this course. It just makes your life easier. We've seen that. yeah. And then the next course.
Thomas Screnci: Yeah, I'll also throw out that we do recommend sometimes to students Coursera online, free courses as well. But Alan brings amazing point of the online brand as resources as well. So either those would be would be wonderful. Here's our our second course.
Alan Cheng: Yeah. Yeah. And there's other ways to learn Python definitely. Data Camp. There, there's a couple of other ways. Yeah. Coursera. 102 is the other course that you might jump into at the beginning of your program here. So it's molecular biology, genetics and disease. It's a graduate Level program that covers kind of modern biology and genomics.
It also teaches you how to read papers. So that's not really listed here. But it teaches you how to read papers, how to critically look at a paper and draw conclusions from it, how to analyze figures, and then it also is, you know, we put in there a gentle introduction to R. So towards the end of the course, you are looking at genomics, data sets and using R to start doing some basic sequence analysis as shown at the bottom. Yeah. And you learn about modern technology, such as Crispr and other methods as well.
So it's a great course to jump into the biology side of things, but with a bit of, I guess, like computational analysis in it. And then the other course is a lot of computation. RBIF 100 is a lot of computational analysis with a little bit of biology put into it.
Thomas Screnci: Thank you, Alan. So that is good introduction to the curriculum, the courses now jumping ahead till maybe the life after graduation, or, you know, just life outside of Brandeis. And would you mind jumping into talking about the bioinfects industry? Please.
Alan Cheng: Yeah, sure.
Slide switches to say "Marketplace Information." Bullet points say: "Bioinformatics market estimated to grow from USD 2.5 billion in 2021 to USD 5.3 billion by 2026. A compound annual growth rate of 13.7% from 2023 to 2030."
Alan Cheng speaks: So there's a bunch of numbers on this page. The Bioinformatics market is growing lot of demand. Certainly. You know, the ability to start ameliorating disease, and there is agricultural applications as well animal applications as well. So the market is growing. The amount of data we have is growing, and the ability to leverage that data do things like data. Science approaches which bioinformatics is essentially a data science discipline.
It was just bioinformatics was around much earlier than data science, at at least as a term, and it's expected to grow quite a bit. There are a lot of biopharma employment hubs, so just 2 that are popular. Actually, a couple that are popular Massachusetts, California. And you can see the growth. There, it's definitely a growing area.
And there are actually hubs popping up all over the world, and throughout the US as well. Yeah, it's definitely growing. It's what I'll say is, there's always gonna be lumps. It's not gonna be like, consistently like, just straight shoot up. But yeah, it's a growing field. There's a lot of demand for it. People with good skill sets that have data. Science, understand biology, understand technology.
Thomas Screnci: Thank you, Alan. Talk a little about the faculty, please.
Slide switches to say "Bioinformatics Faculty." Bullet points list occupations of Brandeis Online faculty: Bioinformatics Engineer IV at Memorial Sloan Kettering Center, Research Fellow at Pfizer, VP of Translational Genomics at Maze Therapeutics and more.
Alan Cheng: Yeah. Yeah. So here's a you know a list of the titles of some of our faculty members. A lot of them come from larger pharma. So like Pfizer, you'll see towards the top, Gilead towards the bottom, Boringer, Ingelheim around the middle, and then smaller biotechs as well. So Maize Therapeutics. You see Medis Therapeutics, Tegenta. And then we have staff or instructors from essentially academic centers. They're usually slightly more industrial, but academic centers. So like memorial Sloan Kettering Cancer Center, where the faculty member works on pipelines and actually analyzes patient data. And then Hopkins, School of Public Health is another one. So yeah, so we, we have a diversity of faculty backgrounds. This helps, you understand, I think, opportunities and the industry better definitely encourage you.
In the courses we always have, we have, you know, the course discussion where you're talking about course material. But we also have an open discussion section where you can ask any general questions about the field and faculty are always enthusiastic to try to answer those, and then you also see that your student cohort you'll you'll see a number of students from other companies, other backgrounds, and those are really helpful insights as well. So it's not just the faculty. Yeah.
Thomas Screnci: Thank you all. I will always like to add, in the fact that our faculty engage with us part time. They work in their field full time. And we can, we basically teach them how to educate an online platform. So the the faculty you see brought up here have amazing experience and a full time experience in their field. So they're bringing that to the online classrooms. That's definitely a great aspect of brand us online to to highlight your other one.
Alan Cheng: Yeah, no, that's a really good point. The faculty are, you know, they have their full time job there. Actually, all of them are excited to teach. And that's why they do this here. Because it's it is extra commitment for them. And yeah, so so yeah, so that's a good group. And I think Brandeis has a good focus on pedagogy and teaching skills, especially for online format. Do you want me to go through the Bioinformatics requirements?
Thomas Screnci: No, I'm happy to, thank you, Alan.
Alan Cheng: Okay. Yeah.
Thomas Screnci: You've given us great information. So thank you.
I was gonna add in in terms of the requirements, is kind of the program structure. We, of course, all our program is 100% online. They are asynchronous or self paced. So there are no set meeting times for our classes you may have to meet with with classmates to do projects on certain classes, certain projects, certain weeks, but everything is self paced.
Course materials are posted on a weekly basis. So typically Wednesday morning early Wednesday morning, you would have the course materials available, and then you'd have the full week to do the work. You know whether you did that Wednesday evening, Saturday at midnight, or whenever you'd have basically a full week to do your work which could be readings. It could be videos, it could be projects to be engaged in. So that greatly depends on what the what the instructor feels is the best method for delivery. What the topic is for the course for that week. So that's important to know. Always a great feature of our program is the self paced the asynchronous aspect of it, and the weekly pace of it as well.
Slide switches to say "Bioinformatics Requirements." Bullet points say: Molecular Biology or Biochemistry; Statistics, Probability, or Biostatistics. We can recommend courses to take if you do not meet prerequisites. NO previous coding experience required.
Tom Screnci speaks: The requirements as you've seen here by now. Molecular biology, biochemistry and stats are great to see coding is good to have, but not required. So if you didn't have that as a coursework that's completely fine. As Alan and I said, there are resources to get that experience. If you would like to do that just makes your life easier as you start the program, but by no means required. And you'll not be denied because you haven't learned python in the past. So outside of that outside of these, rather excuse me. These are the pieces of application we are looking for.
Slide switches to list Application Checklist: 1. Online application, 2. Official transcripts, 3. Resume, 4. Statement of Goals, 5. Letter of Recommendation. No application fee and no GRE/GMAT required.
Tom Screnci speaks: Our next session starts on April second. That's the date classes. Start is April second, with the application deadline for the master's degrees being March 4, th if you were thinking of a certificate, you can typically fill out the certificate, application, form and enroll in the program by March 11th So a little bit more flexibility with the certificate program.
But this checklist applies very much to the master's degrees, but not really to the master's certificate. So that's an important note. The application is, of course, online. There's no application fee, no standardized testing required of you. We do like to have all transcripts from all of your previous institutions, so if you transferred from one school to the other, we would need both or 3, or however many transcripts from you.
We can review applications that make decisions with unofficial transcripts. So if you had a copy that you had saved in the past, we can use that. But we would require an official transcript by the end of your 1st session. So please keep that in mind.
If your university offers previous universities offer official transcripts electronically, sending them to online@brandeis.edu is totally fine. That's the best way to do the most schools do it. But online these days as well. If your school only does paper, I'm happy to share the mailing address for that. But most schools are doing online email delivery these days.
We ask for an official, an official. Excuse me, just a updated resume from you. You can break the standard norms you typically hear of, you know, one page only. It can be 2, 3 pages long, giving us great depth of the projects, the work you've done, the experience you've had in your field. Just showing us your your experience, related or or unrelated to the field. So we can kind of have that context. So resume is is required. If you've done coursework through Coursera other program, professional developments. Rather, you can include that in your resume, too.
We ask for 1500 word or more statement of goals. This is you just saying why you're applying to this program, maybe why Brandeis's program. People might talk about goals after graduation or life changes or their undergraduate experience. So please feel free to give as much context as you feel is appropriate. But if you, if you write just 500 words exactly onto why you're applying to this program and how it's going to benefit you as a professional that's completely that's completely fine. So whatever you think is acceptable. Please feel free to submit. As long as it's 500 words or more.
We request one letter of recommendation. You can submit more. If you have more, you'd like to submit. Your letter of recommendation is preferred to come from a current manager or supervisor. A former manager or supervisor is also acceptable if you don't have one. If you're a recent graduate, as we get plenty of, and you wanted to use someone who maybe oversaw you in an internship or research project. Just a professor, maybe even just a boss at an unrelated job that you had as a student. Those are all fine. The ideal can't. Ideal recommender is a current manager or supervisor. But if you can't come, if you can't do that, or can't come close to that, it's still acceptable to send as close as you can.
Someone who can talk about you in a professional setting is going to be the the ideal candidate. So, however, you feel you like to do that. It's fine. If it's 3 or 4 more recommendations. That's great. But one is completely acceptable for that.
Alan Cheng: I'll just add in that we we do. When we look at the applications. We look at the whole package. Certainly, if there's been some bumps in the road academically, the letters from your you know, supervisor from your manager definitely helps more. So. So just think about the whole package when you get these. Yeah.
Thomas Screnci: Great point out. Thank you for saying that. Yeah, definitely, definitely, the full package. So if undergraduate was rougher or work experiences is shorter, you know, it's definitely the full full package we're looking for. We're considering admissions is rolling admission here, meaning as applications are completed. We review them and send out decisions. Once your application is fully complete and eligible for review. We like to get decisions out to you within a week's time. You know, it's typically around that time, sometimes a little bit shorter, sometimes a little bit longer. Alan and I are working as a team within that, so it can fluctuate. But typically weeks. Time is ours, our goal with the application. So if you completed an application this week for Fall one and we got you a decision, you have, you know, until basically until July to make a decision. So we will get your decision as soon as you're ready. You can wait on your decision. You could move ahead earlier, you could jump right in and deposit and start to move forward.
But we do like to get decisions out to you as quick as possible, just to make your life a little bit easier. So that completes admissions process very straightforward. My, one of my favorite aspects of the program is, it's a very straightforward admissions process making your life a little bit easier, as you consider academic options so definitely consider something to to know.
Slide switches to say "Master's Certificate Checklist." List includes: 1. Master's Certificate Enrollment form, tell us where you work, where you completed your bachelor's degree, current resume. 2. Pay the $500 non-refundable deposit.
Tom Screnci speaks: So that was the Master's degree. If you're thinking of the certificate, there is a certificate application enrollment form on our website. You are just telling us where you worked, you're giving us a resume telling us where you completed your undergraduate experience, and from there it is reviewed, and you're offered admission, or any any follow up questions before offering you the ability to enroll and start in your 1st course.
So this is an even more straightforward process. So again, these 4 certificate courses that you would choose are stackable into the degree. If you did complete a certificate, then decided you wanted it to get a degree. We typically waive the statement of goals. That kind of saves you a little bit of time, and we would still need an official transcript at that point, and we would likely reuse the resume you gave us, unless you wanted to update it so very much a concise process for the certificate application.
For either the certificate or the degree once you are completed and enrolled, we would introduce you to your advisor, who would start you to help you with the registration process what courses to choose based on availability and your interest. But that would be the last step would be after your deposit would be your advisor.
And that completes our our session here. And we're gonna open the floor to any questions you may have. And I always like to end with our email addresses, so you can always write them down or or anything like that. And I'll end the recording in a second. So you can ask as many questions as you like about any specific, maybe private topics you want. But before I end, just want to say thank you to everyone who is attending, thank you for those who have watched this recording, and hope to hear from you soon, so I'll end the recording now, and thank you for joining us.