iiinova — where your digital self keeps evolving

Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 07/10/2026

Behind every published figure is work the reader may never see: data cleaning, quality control, failed attempts, rerun analyses, parameter checks, revised labels and repeated validation. A figure may occupy half a page, but making it scientifically defensible can take weeks.

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 06/10/2026

When should you stop analysing and start writing? When the planned analyses answer the research question, the key checks are complete, and another test is unlikely to change the conclusion. But writing should begin earlier—it often reveals the gaps that genuinely need more analysis.

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 05/10/2026

Finishing experiments means you have results. Finishing a paper means explaining what they support, checking every figure, making the methods reproducible and being honest about uncertainty. The last analysis is rarely the last task. #PhD #Research

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 02/10/2026

Reviewers taught me to ask harder questions of my own work: Does the evidence support the claim? Are the methods clear enough to reproduce? Have I explained the limitations honestly? Feedback can be difficult to read, but it helps me see what readers need from the paper. #PhD #Research

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 30/09/2026

How I manage version control with GitHub: I keep scripts organised by research aim, use clear file names, commit after meaningful changes and document each workflow in the README. For me, GitHub is more than backup—it creates a transparent record of how an analysis develops. #Bioinformatics #GitHub

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 29/09/2026

The hardest part of computational biology is not coding. It is deciding whether the data are suitable, choosing methods, recognising confounding factors and interpreting results without overstating them. Code can produce an answer. Scientific judgement decides whether that answer is meaningful.

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 28/09/2026

Submitting my first manuscript taught me that finishing the analysis is only the beginning. Journal fit matters, limitations must be stated honestly, and every number must remain consistent across the text, figures and supplements. Rejection is difficult, but it can sharpen the science. #PhDLife

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 24/09/2026

Finishing the experiments means the results exist. Finishing the paper means checking them, what they support, explaining the limitations and shaping everything into one clear story. I am learning that the distance between analysis complete and paper complete is much longer than it looks

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 24/09/2026

What reviewers taught me about better science: clarity is part of rigour. A difficult comment can reveal an assumption I did not explain, a limitation I understated or an analysis that needs stronger justification. Revision is not only about improving the paper—it improves the research behind it.

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 23/09/2026

My weekly research routine is a mix of reading papers, writing and checking code, reviewing quality-control results, organising tables and figures, meeting with my supervisors, and documenting every decision. Multi-omics research rarely follows a straight line—each result shapes the next question🧬

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 22/09/2026

How do I organise a multi-omics research project🧬? I divide it into clear aims, keep raw data separate from processed data, give every analysis its own scripts, tables and figures, and document each decision. With several omics layers, organisation is not administration—it is part of reproducibility

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 21/09/2026

The reality of analysing thousands of genes? Most will never become biomarkers. The real work is controlling false discoveries, checking data quality and narrowing a long list to signals that are statistically reliable and biologically meaningful. More genes do not always mean more answers.

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 18/09/2026

What surprised me most during the first month of my PhD was how much research happens before the “results”: checking metadata, cleaning data, questioning assumptions and becoming comfortable with uncertainty. The groundwork may look quiet, but it shapes everything that follows. 🧬

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 17/09/2026

Why multi-omics? Cancer cannot always be understood through gene expression alone. Integrating transcriptomic, epigenetic, clinical and immune data can reveal complementary patterns—but integration must be carefully designed, validated and interpreted without overstating association as a mechanism🧬

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 17/09/2026

I chose cervical cancer research because it sits at the intersection of viral infection, genomics, epigenetics and health inequity. Its strong link with HPV creates opportunities for prevention, while tumour complexity still demands careful molecular research. This is where I hope to contribute. 🧬

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Dalal F. S. A. Alhabad @dalalalhabad.bsky.social · 16/09/2026

Hello, Bluesky! I’m Dalal, a PhD candidate in bioinformatics at La Trobe University. My research explores HPV-associated cervical cancer through multi-omics and cancer genomics. I’m here to connect, learn and share insights on computational oncology and open science. 🧬 #Bioinformatics #CancerGenomic

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